A metabolic map and artificial intelligence-aided identification of nasopharyngeal carcinoma via a single-cell Raman platform.

ABSTRACT:

Background

Nasopharyngeal carcinoma (NPC) is a complex cancer influenced by various factors. This study explores the use of single-cell Raman spectroscopy as a potential diagnostic tool for investigating biomolecular changes associated with NPC carcinogenesis.

Methods

Seven NPC cell lines, one immortalised nasopharyngeal epithelial cell line, six nasopharyngeal mucosa tissues and seven NPC tissue samples were analysed by performing confocal Raman spectroscopic measurements and imaging. The single-cell Raman spectral dataset was used to quantify relevant biomolecules and build machine learning classification models. Metabolomic profiles were investigated using ultra-performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS).

Results

By generating a metabol

SUBMITTER: Xu J 

PROVIDER: S-EPMC11091122 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature