Identification of metabolic biomarkers to predict treatment outcome and disease progression in multiple myeloma

Authors

Ranran Zhao, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.
Yiyu Xie, Yale New Haven Health/Bridgeport Hospital Bridgeport, USA.
Bingyu Yang, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.
Chang Wang, School of Radiation Medicine and Protection, Medical College of Soochow University, Collaborative Innovation Center of Radiological Medicine of Jiangsu Higher Education Institutions, Jiangsu Provincial Key Laboratory of Radiation Medicine and Protection Suzhou, China.
Qianlei Huang, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.
Yue Han, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.
Lulu Yang, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.
Shuang Yan, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.
Xiaogang Wang, Department of Mathematics and Statistics, York University Toronto, Canada.
Chengcheng Fu, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.
Depei Wu, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.
Xiaojin Wu, National Clinical Research Center for Hematologic Diseases, Jiangsu Institute of Hematology, The First Affiliated Hospital of Soochow University Suzhou, China.

Document Type

Article

Publication Title

American journal of cancer research

Abstract

The relationship between metabolites and multiple myeloma (MM) is becoming a research focus in the field. In this study, we performed metabolic profiling of multiple myeloma and identified potential metabolites associated with clinical characteristics, therapeutic efficacy, and prognosis of the disease. Fifty-five patients with newly-diagnosed multiple myeloma and thirty-seven healthy controls from August 2016 to October 2017 were randomly collected. The serum metabolic profiling was investigated by gas chromatography-mass spectrometry (GC-MS) technique and underwent statistical analysis. Twenty-seven metabolites were found to be significantly different between healthy controls and multiple myeloma patients. Eleven metabolites were significantly elevated, while sixteen metabolites were decreased in the multiple myeloma population. Metabolic changes were also observed in patients with renal impairment and bone destruction. Levels of urea were significantly decreased after treatment while levels of hypotaurine showed significant increase in the good-effect group (P<0.05), but not in the no-good-effect group (P>0.05). In multivariate statistical analyses, high cysteine and high hypotaurine are independent risk factors for poor treatment outcome. After adjustment for critical clinical characteristics, patients with high levels of glycolic acid and xylitol were found to be less likely to experience disease progression. Multiple myeloma demonstrates different metabolic characteristics compared with the healthy population. Among multiple myeloma patients, renal impairment and bone destruction showed additional metabolic characteristics. Cysteine and hypotaurine have value in predicting the treatment outcome, while glycolic acid and xylitol may be important prognostic factors for multiple myeloma.

First Page

3935

Last Page

3946

Publication Date

1-1-2020

Recommended Citation

Zhao, Ranran; Xie, Yiyu; Yang, Bingyu; Wang, Chang; Huang, Qianlei; Han, Yue; Yang, Lulu; Yan, Shuang; Wang, Xiaogang; Fu, Chengcheng; Wu, Depei; and Wu, Xiaojin, "Identification of metabolic biomarkers to predict treatment outcome and disease progression in multiple myeloma" (2020). All Research. 134.
https://scholar.bridgeporthospital.org/all_research/134

Identifier

33294278 (pubmed); PMC7716146 (pmc)