{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T20:53:58Z","timestamp":1784235238113,"version":"3.55.0"},"reference-count":46,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2021,3,11]],"date-time":"2021-03-11T00:00:00Z","timestamp":1615420800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Oncol."],"abstract":"<jats:sec><jats:title>Purpose<\/jats:title><jats:p>Gastric cancer is a common tumor of the digestive system. Identification of potential molecules associated with gastric cancer progression and validation of potential biomarkers for gastric cancer diagnosis are very important. Thus, the aim of our study was to determine the serum metabolic characteristics of the serum of patients with chronic gastritis (CG) or gastric cancer (GC) and validate candidate biomarkers for disease diagnosis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Experimental Design<\/jats:title><jats:p>A total of 123 human serum samples from patients with CG or GC were collected for untargeted metabolomic analysis <jats:italic>via<\/jats:italic> UHPLC-Q-TOF\/MS to determine characteristics of the serum. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and heat map were used for multivariate analysis. In addition, commercial databases were used to identify the pathways of metabolites. Differential metabolites were identified based on a heat map with a <jats:italic>t<\/jats:italic>-test threshold (<jats:italic>p<\/jats:italic> &amp;lt; 0.05), fold-change threshold (FC &amp;gt; 1.5 or FC &amp;lt; 2\/3) and variable importance in the projection (VIP &amp;gt;1). Then, differential metabolites were analyzed by receiver operating characteristic (ROC) curve to determine candidate biomarkers. All samples were analyzed for fasting lipid profiles.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Analysis of serum metabolomic profiles indicated that most of the altered metabolic pathways in the three groups were associated with lipid metabolism (<jats:italic>p<\/jats:italic> &amp;lt; 0.05) and lipids and lipid-like molecules were the predominating metabolites within the top 100 differential metabolites (<jats:italic>p<\/jats:italic> &amp;lt; 0.05, FC &amp;gt; 1.5 or FC &amp;lt; 2\/3, and VIP &amp;gt;1). Moreover, differential metabolites, including hexadecasphinganine, linoleamide, and N-Hydroxy arachidonoyl amine had high diagnostic performance according to PLS-DA. In addition, fasting lipid profile analysis showed the serum levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A1 (Apo-A1) were decreased concomitant to the progression of the progression of the disease compared with those in the control group (<jats:italic>p<\/jats:italic> &amp;lt; 0.05).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Thus, this study demonstrated that lipid metabolism may influence the development of CG to GC. Hexadecasphinganine, linoleamide, and N-Hydroxy arachidonoyl amine were selected as candidate diagnostic markers for CG and GC.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fonc.2021.636917","type":"journal-article","created":{"date-parts":[[2021,3,11]],"date-time":"2021-03-11T07:49:38Z","timestamp":1615448978000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":49,"title":["Serum Metabolic Profiling Analysis of Chronic Gastritis and Gastric Cancer by Untargeted Metabolomics"],"prefix":"10.3389","volume":"11","author":[{"given":"Lin","family":"Yu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinhuai","family":"Lai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanmeng","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiafu","family":"Feng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bei","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2021,3,11]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.2147\/CMAR.S149619","article-title":"Gastric cancer: epidemiology, prevention, classification, and treatment","volume":"10","author":"Sitarz","year":"2018","journal-title":"Cancer Manag Res"},{"key":"B2","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1111\/j.1523-5378.2011.00880.x","article-title":"Gastric cancer: clinical aspects, epidemiology and molecular background","volume":"16","author":"Bornschein","year":"2011","journal-title":"Helicobacter"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000005887","article-title":"Gastric cancer burden of last 40 years in North China (Hebei Province): A population-based study","volume":"96","author":"Liang","year":"2017","journal-title":"Med (Baltimore)"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1002\/cam4.2055","article-title":"Serum biomarker panels for the diagnosis of gastric cancer","volume":"8","author":"Wu","year":"2019","journal-title":"Cancer Med"},{"key":"B5","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1007\/s10120-013-0259-5","article-title":"Clinical significance of serum tumor markers for gastric cancer: a systematic review of literature by the Task Force of the Japanese Gastric Cancer Association","volume":"17","author":"Shimada","year":"2014","journal-title":"Gastric Cancer"},{"key":"B6","doi-asserted-by":"publisher","first-page":"737","DOI":"10.1186\/s12885-017-3738-y","article-title":"Diagnostic and prognostic value of CEA, CA19\u20139, AFP and CA125 for early gastric cancer","volume":"17","author":"Feng","year":"2017","journal-title":"BMC Cancer"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1245\/s10434-016-5717-y","article-title":"Use of Tumor Markers in Gastrointestinal Cancers: Surgeon Perceptions and Cost-Benefit Trade-Off Analysis","volume":"24","author":"Acharya","year":"2017","journal-title":"Ann Surg Oncol"},{"key":"B8","doi-asserted-by":"publisher","first-page":"733","DOI":"10.3390\/cancers11050733","article-title":"Clinical Evaluation of CA72-4 for Screening Gastric Cancer in A Healthy Population: A Multicenter Retrospective Study","volume":"11","author":"Hu","year":"2019","journal-title":"Cancers"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.1007\/s13361-016-1469-y","article-title":"Untargeted Metabolomics Strategies-Challenges and Emerging Directions","volume":"27","author":"Schrimpe-Rutledge","year":"2016","journal-title":"J Am Soc Mass Spectrom"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2016.12.039","article-title":"Understanding the Intersections between Metabolism and Cancer Biology","volume":"168","author":"Vander Heiden","year":"2017","journal-title":"Cell"},{"key":"B11","doi-asserted-by":"publisher","first-page":"102","DOI":"10.3390\/metabo9050102","article-title":"Breast Cancer Metabolomics: From Analytical Platforms to Multivariate Data Analysis. 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