Metabolomic Profiling Identified Serum Metabolite Biomarkers and Related Metabolic Pathways of Colorectal Cancer

Zhang, Chengjian; Zhou, Shengnan; Chang, Huijing; Zhuang, Feng; Shi, Yang; Chang, Le; Ai, Wanchao; Du, Juan; Liu, Wei; Liu, Humin; Zhou, Xukun; Wang, Zhong; Hong, Tao

doi:10.1155/2021/6858809

Cited by 25 publications

(18 citation statements)

References 51 publications

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“…To increase the sensitivity and specificity in predicting colorectal cancer and improve the understanding of the pathological mechanism of colorectal cancer development, efforts have been made to discover protein and metabolite biomarkers. Recent studies have reported that potential metabolite biomarkers show dysregulated levels in the blood of colorectal cancer patients compared with healthy controls. − , However, most of these studies only focus on identifying biomarkers between colorectal cancer and healthy controls . One of the studies grouped the patients based on the risk of colorectal cancer precursors (including conventional adenomas and serrated polyps) and found that lipid metabolism and metabolites may be involved in the early stage of serrated pathway-related colorectal carcinogenesis .…”

Section: Resultsmentioning

confidence: 99%

Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry

et al. 2023

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A major challenge in reducing the death rate of colorectal cancer is to screen patients using low-invasive testing. A blood test shows a high compliance rate with reduced invasiveness. In this work, a multiplex isobaric tag labeling strategy coupled with mass spectrometry is adopted to relatively quantify primary and secondary amine-containing metabolites in serum for the discovery of metabolite level changes of colorectal cancer. Serum samples from patients at different risk statuses and colorectal cancer growth statuses are studied. Metabolite identification is based on accurate mass matching and/or retention time of labeled metabolite standards. We quantify 40 metabolites across all the serum samples, including 18 metabolites validated with standards. We find significantly decreased levels of threonine and asparagine in the patients with growing adenomas or high-risk adenomas (p < 0.05). Glutamine levels decrease in patients with adenomas of unknown growth status or high-risk adenomas. In contrast, arginine levels are elevated in patients with low-risk adenoma. Receiver operating characteristic analysis shows high sensitivity and specificity of these metabolites for detecting growing adenomas. Based on these results, we conclude that a few metabolites identified here might contribute to distinguishing colorectal patients with growing adenomas from normal individuals and patients with unknown growth status of adenomas.

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Section: Resultsmentioning

confidence: 99%

Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry

et al. 2023

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“…COAD is a common cause of cancer-related death worldwide, and some studies have constructed prognostic models for immune-related genes ( 30 ). And through the metabolomics analysis of determining the serum metabolite biomarkers and related metabolic pathways in COAD ( 31 ), which helps to improve the prognostic outcomes of COAD patients. Therefore, a comprehensive comprehensive analysis of immune and metabolic gene characteristics in COAD may help us to further explore the methods and pathways to improve the prognosis of COAD patients and improve the effectiveness of immunotherapy.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of prognostic models for colon adenocarcinoma based on combined immune-and metabolism-related genes

Jiang

Yang²,

Jiang³

et al. 2022

Front. Oncol.

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BackgroundThe heterogeneity of tumor tissue is one of the reasons for the poor effect of tumor treatment, which is mainly affected by the tumor immune microenvironment and metabolic reprogramming. But more research is needed to find out how the tumor microenvironment (TME) and metabolic features of colon adenocarcinoma (COAD) are related.MethodsWe obtained the transcriptomic and clinical data information of COAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Consensus clustering analysis was used to identify different molecular subtypes, identify differentially expressed genes (DEGs) associated with immune-and metabolism-related genes (IMRGs) prognosis. Univariate and multivariable Cox regression analysis and Lasso regression analysis were applied to construct the prognostic models based on the IMRG risk score. The correlations between risk scores and TME, immune cell infiltration, and immune checkpoint genes were investigated. Lastly, potential appropriate drugs related to the risk score were screened by drug sensitivity analysis.ResultsBy consensus clustering analysis, we identified two distinct molecular subtypes. It was also found that the multilayered IMRG subtypes were associated with the patient’s clinicopathological characteristics, prognosis, and TME cell infiltration characteristics. Meanwhile, a prognostic model based on the risk score of IMRGs was constructed and its predictive power was verified internally and externally. Clinicopathological analysis and nomogram give it better clinical guidance. The IMRG risk score plays a key role in immune microenvironment infiltration. Patients in the high-risk groups of microsatellite instability (MSI) and tumor mutational burden (TMB) were found to, although with poor prognosis, actively respond to immunotherapy. Furthermore, IMRG risk scores were significantly associated with immune checkpoint gene expression. The potential drug sensitivity study helps come up with and choose a chemotherapy treatment plan.ConclusionOur comprehensive analysis of IMRG signatures revealed a broad range of regulatory mechanisms affecting the tumor immune microenvironment (TIME), immune landscape, clinicopathological features, and prognosis. And to explore the potential drugs for immunotherapy. It will help to better understand the molecular mechanisms of COAD and provide new directions for disease treatment.

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“…Studies have shown that 12,13-DHOME comes from the oxidation of linoleic acid, which is related to an increased risk of ovarian cancer, cytochrome P450 monooxygenase oxidizes linoleic acid to produce 12,13-DHOME, the role of DHOME in multiple cellular functions may lead to an increased risk of ovarian cancer ( Hada et al, 2019 ). 12-Hydroxydodecanoic acid is one of the biomarkers of serum metabolites of colorectal cancer ( Zhang et al, 2021 ). Indole-3 acetaldehyde is a precursor molecule for tryptophan to form endogenous 6-formylindolo [3,2-b] carbazole (ficz), tryptophan is related to tumor immune escape ( Rannug, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

Comprehensive serum metabolomics and network analysis to reveal the mechanism of gypenosides in treating lung cancer and enhancing the pharmacological effects of cisplatin

Xiao

Xie

et al. 2022

Front. Pharmacol.

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Gypenosides (GYP) exerted anticancer activity against various cancers. However, the mechanism of GYP against lung cancer (LC) in vivo remains unclear. This study aims to reveal the potential mechanism of GYP against LC and enhancing cisplatin efficacy using a comprehensive analysis of metabolomics, network analysis. Pharmacodynamic results showed that GYP inhibited tumor growth, reduced tumor volume and tumor weight, and alleviated pathological symptoms in Lewis tumor-bearing mice, and GYP could enhance the anti-LC effects of cisplatin. Using serum metabolomics methods, 53 metabolites were found to be significantly altered in the model group, and the levels of 23 biomarkers were significantly restored after GYP treatment. GYP-related metabolic pathways involved six pathways, including alpha-linolenic acid metabolism, glutathione metabolism, sphingolipid metabolism, glycerophospholipid metabolism, tryptophan metabolism, and primary bile acid biosynthesis. 57 genes associated with differential metabolites of GYP recovery and 7 genes of 11 saponins of GYP against LC were screened by network analysis, the STRING database was used to find the association between 57 genes and 7 genes, and a compound-intersection gene-metabolite related gene-metabolite-pathway network was constructed, and STAT3, MAPK14, EGFR and TYMS might be the crucial targets of GYP against LC. Western blot results showed that GYP restored the levels of STA3, MAPK14, EGFR, and TYMS in the model group, and GYP also restored the levels of STAT3 and MAPK14 in the cisplatin group, indicating that GYP might exert anti-LC effects and enhance the pharmacological effects of cisplatin through MAPK14/STAT3 signaling pathway. Our method revealed the effect and mechanism of GYP on LC and the pharmacological effects of GYP-enhanced chemotherapeutic agent cisplatin, which provided some reference for the development of anti-cancer drugs.

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Metabolomic Profiling Identified Serum Metabolite Biomarkers and Related Metabolic Pathways of Colorectal Cancer

Cited by 25 publications

References 51 publications

Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry

Quantification of Serum Metabolites in Early Colorectal Adenomas Using Isobaric Labeling Mass Spectrometry

Development and validation of prognostic models for colon adenocarcinoma based on combined immune-and metabolism-related genes

Comprehensive serum metabolomics and network analysis to reveal the mechanism of gypenosides in treating lung cancer and enhancing the pharmacological effects of cisplatin

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