Diagnosis and prognosis of breast cancer by high-performance serum metabolic fingerprints

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Significance: Breast cancer (BrCa) is the most common cancer worldwide, and high-performance metabolic analysis is emerging in diagnosis and prognosis of BrCa. Here, we used nanoparticle-enhanced laser desorption/ionization mass spectrometry to record serum metabolic fingerprints of BrCa in seconds, achieving high reproducibility and low consumption of direct serum detection. Our analytical method, combined with the aid of machine learning algorithms, was demonstrated to provide high diagnostic efficiency with accuracy of 88.8% and desirable prognostic prediction ( P < 0.005). Furthermore, seven metabolic biomarkers differentially enriched in BrCa serum and their related pathways were identified. Together, our findings provide a tool to characterize BrCa and highlight certain metabolic signatures as potential diagnostic and prognostic factors of diseases including but not limited to BrCa.
Funding Information
  • National Natural Science Foundation of China (82073269, 81772802, and M-0349)
  • National Natural Science Foundation of China (81771983 and 81971771)
  • Ministry of Science and Technology of the People''''s Republic of China (2017YFE0124400 and 2018YFC1312800)
  • Shanghai Institutions of Higher Learning (2021-01-07-00-02-E00083)
  • Shanghai Science and Technology Innovation Active Plan (20XD1402800)
  • Clinical Research Plan of SHDC (SHDC2020CR2065B)
  • Shanghai Rising-Star Program (19QA1404800)
  • Innovation Research Plan by the Shanghai Municipal Education Commission (ZXWF082101)
  • Clinical Research Innovation Plan of Shanghai General Hospital (CTCCR-2016B05)
  • Natural Science Fundation of Jiangsu Province (BK20181186)
  • Shanghai Science and Technology Commission (20JC1410100)

This publication has 52 references indexed in Scilit: