Serum Metabolomics Reveals Dysregulation and Diagnostic Potential of Oxylipins in Tumor-Induced Osteomalacia

Author:

Gong Yiyi12ORCID,Ni Xiaolin1,Jin Chenxi1,Li Xiang1,Wang Yujie2,Wang Ou1,Li Mei1,Xing Xiaoping1,Wu Zhihong2,Jiang Yan1,Xia Weibo1ORCID

Affiliation:

1. Department of Endocrinology, Key Laboratory of Endocrinology, National Commission of Health, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China

2. Medical Research Center, National Commission of Health, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing 100730, China

Abstract

Abstract Context Excessive production of fibroblast growth factor 23 (FGF23) by a tumor is considered the main pathogenesis in tumor-induced osteomalacia (TIO). Despite its importance to comprehensive understanding of pathogenesis and diagnosis, the regulation of systemic metabolism in TIO remains unclear. Objective We aimed to systematically characterize the metabolome alteration associated with TIO. Methods By means of liquid chromatography–tandem mass spectrometry–based metabolomics, we analyzed the metabolic profile from 96 serum samples (32 from TIO patients at initial diagnosis, pairwise samples after tumor resection, and 32 matched healthy control (HC) subjects). In order to screen and evaluate potential biomarkers, statistical analyses, pathway enrichment and receiver operating characteristic (ROC) were performed. Results Metabolomic profiling revealed distinct alterations between TIO and HC cohorts. Differential metabolites were screened and conducted to functional clustering and annotation. A significantly enriched pathway was found involving arachidonic acid metabolism. A combination of 5 oxylipins, 4-HDoHE, leukotriene B4, 5-HETE, 17-HETE, and 9,10,13-TriHOME, demonstrated a high sensitivity and specificity panel for TIO prediction screened by random forest algorithm (AUC = 0.951; 95% CI, 0.827-1). Supported vector machine modeling and partial least squares modeling were conducted to validate the predictive capabilities of the diagnostic panel. Conclusion Metabolite profiling of TIO showed significant alterations compared with HC. A high-sensitivity and high-specificity panel with 5 oxylipins was tested as diagnostic predictor. For the first time, we provide the global profile of metabolomes and identify potential diagnostic biomarkers of TIO. The present work may offer novel insights into the pathogenesis of TIO.

Funder

Beijing Municipal Natural Science Foundation

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

The Endocrine Society

Subject

Biochemistry (medical),Clinical Biochemistry,Endocrinology,Biochemistry,Endocrinology, Diabetes and Metabolism

Reference43 articles.

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