2021
DOI: 10.1038/s41416-021-01395-w
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Identification of diagnostic markers and lipid dysregulation in oesophageal squamous cell carcinoma through lipidomic analysis and machine learning

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Cited by 14 publications
(11 citation statements)
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“…In recent years, as development in algorithms, machine learning is becoming more and more widely employed in data mining procedures of metabolomics to retrieve biomarker panels for better performance ( Reel et al, 2021 ; Li et al, 2022 ). For example, researchers have used support vector machine (SVM)-based machine learning models to illustrate diagnostic biomarkers in blood for oesophageal cancer ( Yuan et al, 2021 ), pancreatic cancer ( Wang et al, 2021 ), lung cancer ( Wang et al, 2022 ) and brain glioma ( Zhou et al, 2022 ). The SVM-based algorithm can rank all potential biomarkers according to their weight in the model, making it practical to optimize the candidates for a biomarker panel.…”
Section: Discussionmentioning
confidence: 99%
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“…In recent years, as development in algorithms, machine learning is becoming more and more widely employed in data mining procedures of metabolomics to retrieve biomarker panels for better performance ( Reel et al, 2021 ; Li et al, 2022 ). For example, researchers have used support vector machine (SVM)-based machine learning models to illustrate diagnostic biomarkers in blood for oesophageal cancer ( Yuan et al, 2021 ), pancreatic cancer ( Wang et al, 2021 ), lung cancer ( Wang et al, 2022 ) and brain glioma ( Zhou et al, 2022 ). The SVM-based algorithm can rank all potential biomarkers according to their weight in the model, making it practical to optimize the candidates for a biomarker panel.…”
Section: Discussionmentioning
confidence: 99%
“…Metabolomic studies have made great progresses recently in tumor diagnosis. Yuan et al (2021) combined serum lipidomics to reveal lipid biomarkers for detection of oesophageal squamous cell carcinoma, and a panel of 12 lipids were finally found for diagnostic purpose. Wang et al (2021) employed metabolomics in search for blood diagnostic biomarkers of pancreatic ductal adenocarcinoma and early-stage lung adenocarcinoma ( Wang et al, 2022 ), revealing 17 and 9 potential lipid markers in blood separately.…”
Section: Introductionmentioning
confidence: 99%
“…We were able to identify correlations between pathological conditions, expression of DPPC, and expression of ANXA2 in a variety of reports (Table 1). Both increased DPPC and decreased ANXA2 have been associated with esophageal cancer, 84,85 osteosarcoma, 86,87 and non‐malignance of salivary tumors 88,89 . Also interesting is a possible association of DPPC and ANXA2 in both lupus and preeclampsia, where increased DPPC can accumulate to form “active hydrophobic spots,” possibly in conjunction with antiphospholipid syndrome and development of autoantibodies against ANXA2 90–94 .…”
Section: Discussionmentioning
confidence: 99%
“…Interestingly, we were able to identify correlations between pathological conditions, expression of DPPC, and expression of ANXA2 in a variety of reports (Table 2). Both increased DPPC and decreased ANXA2 have been associated with esophageal cancer, 75, 76 osteosarcoma, 77, 78 and non-malignance of salivary tumors. 79, 80 Also interesting is a possible association of DPPC and ANXA2 in both lupus and preeclampsia, where increased DPPC can accumulate to form “active hydrophobic spots,” possibly in conjunction with antiphospholipid syndrome and development of autoantibodies against ANXA2.…”
Section: Discussionmentioning
confidence: 99%