Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection
 
research article

NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection

Zhao, Yan
•
Ma, Changchun
•
Cai, Rongzhi
Show more
March 19, 2024
Nature Communications

Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. Here, we conduct NMR- and MS-based metabolomics on 1,153 matched ESCC tissues, normal mucosae, pre- and one-week post-operative sera and urines from 560 participants across three hospitals, with machine learning and WGCNA. Aberrations in 'alanine, aspartate and glutamate metabolism' proved to be prevalent throughout the ESCC evolution, consistently identified by NMR and MS, and reflected in 16 serum and 10 urine metabolic signatures in both discovery and validation sets. NMR-based simplified panels of any five serum or urine metabolites outperform clinical serological tumor markers (AUC = 0.984 and 0.930, respectively), and are effective in distinguishing early-stage ESCC in test set (serum accuracy = 0.994, urine accuracy = 0.879). Collectively, NMR-based biofluid screening can reveal characteristic metabolic events of ESCC and be feasible for early detection (ChiCTR2300073613).|Metabolic changes often occur during the early stages of cancer development. Here, the authors develop metabolomics signatures from tissues, pre- and post-operative sera and urines in esophageal squamous cell carcinoma, which may aid in early diagnosis.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

document.pdf

Type

Publisher's Version

Version

Published version

Access type

openaccess

License Condition

CC BY

Size

14.63 MB

Format

Adobe PDF

Checksum (MD5)

b9c723de7f8f0178551deb819dfca3fe

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés