Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics
Abstract Background The morbidity of cancer keeps growing worldwide, and among that, the colorectal cancer (CRC) has jumped to third. Existing early screening tests for CRC are limited. The aim of this study was to develop a diagnostic strategy for CRC by plasma metabolomics. Methods A targeted amin...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2023-11-01
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| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12967-023-04604-7 |
| _version_ | 1797556836107288576 |
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| author | Yang Yang Zhipeng Wang Xinxing Li Jianfeng Lv Renqian Zhong Shouhong Gao Feng Zhang Wansheng Chen |
| author_facet | Yang Yang Zhipeng Wang Xinxing Li Jianfeng Lv Renqian Zhong Shouhong Gao Feng Zhang Wansheng Chen |
| author_sort | Yang Yang |
| collection | DOAJ |
| description | Abstract Background The morbidity of cancer keeps growing worldwide, and among that, the colorectal cancer (CRC) has jumped to third. Existing early screening tests for CRC are limited. The aim of this study was to develop a diagnostic strategy for CRC by plasma metabolomics. Methods A targeted amino acids metabolomics method was developed to quantify 32 plasma amino acids in 130 CRC patients and 216 healthy volunteers, to identify potential biomarkers for CRC, and an independent sample cohort comprising 116 CRC subjects, 33 precancerosiss patients and 195 healthy volunteers was further used to validate the diagnostic model. Amino acids-related genes were retrieved from Gene Expression Omnibus and Molecular Signatures Database and analyzed. Results Three were chosen out of the 32 plasma amino acids examined. The tryptophan / sarcosine / glutamic acid -based receiver operating characteristic (ROC) curve showed the area under the curve (AUC) of 0.955 (specificity 83.3% and sensitivity 96.8%) for all participants, and the logistic regression model were used to distinguish between early stage (I and II) of CRC and precancerosiss patients, which showed superiority to the commonly used carcinoembryonic antigen. The GO and KEGG enrichment analysis proved many alterations in amino acids metabolic pathways in tumorigenesis. Conclusion This altered plasma amino acid profile could effectively distinguish CRC patients from precancerosiss patients and healthy volunteers with high accuracy. Prognostic tests based on the tryptophan/sarcosine/glutamic acid biomarkers in the large population could assess the clinical significance of CRC early detection and intervention. Graphical Abstract |
| first_indexed | 2024-03-10T17:07:43Z |
| format | Article |
| id | doaj.art-3db3ce06627c4a5d9037044dadf97b9b |
| institution | Directory Open Access Journal |
| issn | 1479-5876 |
| language | English |
| last_indexed | 2024-03-10T17:07:43Z |
| publishDate | 2023-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj.art-3db3ce06627c4a5d9037044dadf97b9b2023-11-20T10:44:23ZengBMCJournal of Translational Medicine1479-58762023-11-0121111410.1186/s12967-023-04604-7Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomicsYang Yang0Zhipeng Wang1Xinxing Li2Jianfeng Lv3Renqian Zhong4Shouhong Gao5Feng Zhang6Wansheng Chen7Department of Pharmacy, Second Affiliated Hospital of Naval Medical UniversityDepartment of Pharmacy, Second Affiliated Hospital of Naval Medical UniversityDepartment of General Surgery, Tongji Hospital, Tongji UniversityDepartment of Pharmacy, Taixing People’s HospitalDepartment of Laboratory Medicine, Second Affiliated Hospital of Naval Medical UniversityDepartment of Pharmacy, Second Affiliated Hospital of Naval Medical UniversityDepartment of Pharmacy, Second Affiliated Hospital of Naval Medical UniversityDepartment of Pharmacy, Second Affiliated Hospital of Naval Medical UniversityAbstract Background The morbidity of cancer keeps growing worldwide, and among that, the colorectal cancer (CRC) has jumped to third. Existing early screening tests for CRC are limited. The aim of this study was to develop a diagnostic strategy for CRC by plasma metabolomics. Methods A targeted amino acids metabolomics method was developed to quantify 32 plasma amino acids in 130 CRC patients and 216 healthy volunteers, to identify potential biomarkers for CRC, and an independent sample cohort comprising 116 CRC subjects, 33 precancerosiss patients and 195 healthy volunteers was further used to validate the diagnostic model. Amino acids-related genes were retrieved from Gene Expression Omnibus and Molecular Signatures Database and analyzed. Results Three were chosen out of the 32 plasma amino acids examined. The tryptophan / sarcosine / glutamic acid -based receiver operating characteristic (ROC) curve showed the area under the curve (AUC) of 0.955 (specificity 83.3% and sensitivity 96.8%) for all participants, and the logistic regression model were used to distinguish between early stage (I and II) of CRC and precancerosiss patients, which showed superiority to the commonly used carcinoembryonic antigen. The GO and KEGG enrichment analysis proved many alterations in amino acids metabolic pathways in tumorigenesis. Conclusion This altered plasma amino acid profile could effectively distinguish CRC patients from precancerosiss patients and healthy volunteers with high accuracy. Prognostic tests based on the tryptophan/sarcosine/glutamic acid biomarkers in the large population could assess the clinical significance of CRC early detection and intervention. Graphical Abstracthttps://doi.org/10.1186/s12967-023-04604-7Colorectal cancerAmino acidsTargeted metabolomicsDiagnostic modelTranscriptome |
| spellingShingle | Yang Yang Zhipeng Wang Xinxing Li Jianfeng Lv Renqian Zhong Shouhong Gao Feng Zhang Wansheng Chen Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics Journal of Translational Medicine Colorectal cancer Amino acids Targeted metabolomics Diagnostic model Transcriptome |
| title | Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics |
| title_full | Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics |
| title_fullStr | Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics |
| title_full_unstemmed | Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics |
| title_short | Profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics |
| title_sort | profiling the metabolic disorder and detection of colorectal cancer based on targeted amino acids metabolomics |
| topic | Colorectal cancer Amino acids Targeted metabolomics Diagnostic model Transcriptome |
| url | https://doi.org/10.1186/s12967-023-04604-7 |
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