Plasma Lipidomics Profiling Reveals Biomarkers for Papillary Thyroid Cancer Diagnosis
The objective of this study was to identify potential biomarkers and possible metabolic pathways of malignant and benign thyroid nodules through lipidomics study. A total of 47 papillary thyroid carcinomas (PTC) and 33 control check (CK) were enrolled. Plasma samples were collected for UPLC-Q-TOF MS...
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Frontiers Media S.A.
2021-06-01
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| Series: | Frontiers in Cell and Developmental Biology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcell.2021.682269/full |
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| author | Nan Jiang Zhenya Zhang Xianyang Chen Guofen Zhang Ying Wang Lijie Pan Chengping Yan Guoshan Yang Li Zhao Jiarui Han Teng Xue |
| author_facet | Nan Jiang Zhenya Zhang Xianyang Chen Guofen Zhang Ying Wang Lijie Pan Chengping Yan Guoshan Yang Li Zhao Jiarui Han Teng Xue |
| author_sort | Nan Jiang |
| collection | DOAJ |
| description | The objective of this study was to identify potential biomarkers and possible metabolic pathways of malignant and benign thyroid nodules through lipidomics study. A total of 47 papillary thyroid carcinomas (PTC) and 33 control check (CK) were enrolled. Plasma samples were collected for UPLC-Q-TOF MS system detection, and then OPLS-DA model was used to identify differential metabolites. Based on classical statistical methods and machine learning, potential biomarkers were characterized and related metabolic pathways were identified. According to the metabolic spectrum, 13 metabolites were identified between PTC group and CK group, and a total of five metabolites were obtained after further screening. Its metabolic pathways were involved in glycerophospholipid metabolism, linoleic acid metabolism, alpha-linolenic acid metabolism, glycosylphosphatidylinositol (GPI)—anchor biosynthesis, Phosphatidylinositol signaling system and the metabolism of arachidonic acid metabolism. The metabolomics method based on PROTON nuclear magnetic resonance (NMR) had great potential for distinguishing normal subjects from PTC. GlcCer(d14:1/24:1), PE-NME (18:1/18:1), SM(d16:1/24:1), SM(d18:1/15:0), and SM(d18:1/16:1) can be used as potential serum markers for the diagnosis of PTC. |
| first_indexed | 2024-12-19T10:43:55Z |
| format | Article |
| id | doaj.art-4ca83d9d78d8466baceb3a96080736a8 |
| institution | Directory Open Access Journal |
| issn | 2296-634X |
| language | English |
| last_indexed | 2024-12-19T10:43:55Z |
| publishDate | 2021-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cell and Developmental Biology |
| spelling | doaj.art-4ca83d9d78d8466baceb3a96080736a82022-12-21T20:25:20ZengFrontiers Media S.A.Frontiers in Cell and Developmental Biology2296-634X2021-06-01910.3389/fcell.2021.682269682269Plasma Lipidomics Profiling Reveals Biomarkers for Papillary Thyroid Cancer DiagnosisNan Jiang0Zhenya Zhang1Xianyang Chen2Guofen Zhang3Ying Wang4Lijie Pan5Chengping Yan6Guoshan Yang7Li Zhao8Jiarui Han9Teng Xue10Department of General Surgery, First Hospital of Tsinghua University, Beijing, ChinaDepartment of General Surgery, First Hospital of Tsinghua University, Beijing, ChinaBaoFeng Key Laboratory of Genetics and Metabolism, Beijing, ChinaDepartment of General Surgery, First Hospital of Tsinghua University, Beijing, ChinaDepartment of Oncology, Tai’an City Central Hospital, Tai’an, ChinaDepartment of General Surgery, First Hospital of Tsinghua University, Beijing, ChinaDepartment of General Surgery, First Hospital of Tsinghua University, Beijing, ChinaDepartment of General Surgery, First Hospital of Tsinghua University, Beijing, ChinaDepartment of General Surgery, First Hospital of Tsinghua University, Beijing, ChinaBaoFeng Key Laboratory of Genetics and Metabolism, Beijing, ChinaZhongguancun Biological and Medical Big Data Center, Beijing, ChinaThe objective of this study was to identify potential biomarkers and possible metabolic pathways of malignant and benign thyroid nodules through lipidomics study. A total of 47 papillary thyroid carcinomas (PTC) and 33 control check (CK) were enrolled. Plasma samples were collected for UPLC-Q-TOF MS system detection, and then OPLS-DA model was used to identify differential metabolites. Based on classical statistical methods and machine learning, potential biomarkers were characterized and related metabolic pathways were identified. According to the metabolic spectrum, 13 metabolites were identified between PTC group and CK group, and a total of five metabolites were obtained after further screening. Its metabolic pathways were involved in glycerophospholipid metabolism, linoleic acid metabolism, alpha-linolenic acid metabolism, glycosylphosphatidylinositol (GPI)—anchor biosynthesis, Phosphatidylinositol signaling system and the metabolism of arachidonic acid metabolism. The metabolomics method based on PROTON nuclear magnetic resonance (NMR) had great potential for distinguishing normal subjects from PTC. GlcCer(d14:1/24:1), PE-NME (18:1/18:1), SM(d16:1/24:1), SM(d18:1/15:0), and SM(d18:1/16:1) can be used as potential serum markers for the diagnosis of PTC.https://www.frontiersin.org/articles/10.3389/fcell.2021.682269/fullpapillary thyroid carcinomapathwaylipidomicsplasma samplesorthogonal partial least square discriminant analysis |
| spellingShingle | Nan Jiang Zhenya Zhang Xianyang Chen Guofen Zhang Ying Wang Lijie Pan Chengping Yan Guoshan Yang Li Zhao Jiarui Han Teng Xue Plasma Lipidomics Profiling Reveals Biomarkers for Papillary Thyroid Cancer Diagnosis Frontiers in Cell and Developmental Biology papillary thyroid carcinoma pathway lipidomics plasma samples orthogonal partial least square discriminant analysis |
| title | Plasma Lipidomics Profiling Reveals Biomarkers for Papillary Thyroid Cancer Diagnosis |
| title_full | Plasma Lipidomics Profiling Reveals Biomarkers for Papillary Thyroid Cancer Diagnosis |
| title_fullStr | Plasma Lipidomics Profiling Reveals Biomarkers for Papillary Thyroid Cancer Diagnosis |
| title_full_unstemmed | Plasma Lipidomics Profiling Reveals Biomarkers for Papillary Thyroid Cancer Diagnosis |
| title_short | Plasma Lipidomics Profiling Reveals Biomarkers for Papillary Thyroid Cancer Diagnosis |
| title_sort | plasma lipidomics profiling reveals biomarkers for papillary thyroid cancer diagnosis |
| topic | papillary thyroid carcinoma pathway lipidomics plasma samples orthogonal partial least square discriminant analysis |
| url | https://www.frontiersin.org/articles/10.3389/fcell.2021.682269/full |
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