Correlation Engine 2.0
Clear Search sequence regions

  • gold (2)
  • humans (1)
  • medulloblastoma (4)
  • palladium (2)
  • patient (3)
  • serum (1)
  • treatment effect (1)
  • Sizes of these terms reflect their relevance to your search.

    Diagnostics is the key in screening and treatment of cancer. As an emerging tool in precision medicine, metabolic analysis detects end products of pathways, and thus is more distal than proteomic/genetic analysis. However, metabolic analysis is far from ideal in clinical diagnosis due to the sample complexity and metabolite abundance in patient specimens. A further challenge is real-time and accurate tracking of treatment effect, e.g., radiotherapy. Here, Pd-Au synthetic alloys are reported for mass-spectrometry-based metabolic fingerprinting and analysis, toward medulloblastoma diagnosis and radiotherapy evaluation. A core-shell structure is designed using magnetic core particles to support Pd-Au alloys on the surface. Optimized synthetic alloys enhance the laser desorption/ionization efficacy and achieve direct detection of 100 nL of biofluids in seconds. Medulloblastoma patients are differentiated from healthy controls with average diagnostic sensitivity of 94.0%, specificity of 85.7%, and accuracy of 89.9%, by machine learning of metabolic fingerprinting. Furthermore, the radiotherapy process of patients is monitored and a preliminary panel of serum metabolite biomarkers is identified with gradual changes. This work will lead to the application-driven development of novel materials with tailored structural design and establishment of new protocols for precision medicine in near future. © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


    Jing Cao, Xuejiao Shi, Deepanjali D Gurav, Lin Huang, Haiyang Su, Keke Li, Jingyang Niu, Mengji Zhang, Qian Wang, Mawei Jiang, Kun Qian. Metabolic Fingerprinting on Synthetic Alloys for Medulloblastoma Diagnosis and Radiotherapy Evaluation. Advanced materials (Deerfield Beach, Fla.). 2020 Jun;32(23):e2000906

    Expand section icon Mesh Tags

    Expand section icon Substances

    PMID: 32342553

    View Full Text