Non-Small Cell Lung Cancer Detection and Subtyping by UPLC-HRMS-Based Tissue Metabolomics

Area of Science:

• Metabolomics
• Biochemistry
• Oncology

Background:

• Non-small cell lung cancer (NSCLC) is the most common lung cancer subtype.
• Accurate histological subtyping (adenocarcinoma vs. squamous cell carcinoma) is crucial for treatment decisions.

Purpose of the Study:

• To utilize ultraperformance liquid chromatography-high-resolution mass spectrometry (UPLC-HRMS) for metabolic profiling of NSCLC tissues.
• To identify discriminant metabolite panels for distinguishing NSCLC subtypes and normal lung tissue.
• To validate the diagnostic and subtyping capabilities of the identified metabolite panels.

Main Methods:

• Metabolic profiling of 227 NSCLC tissue samples (adenocarcinoma and squamous cell carcinoma) and adjacent/distant noncancerous tissues using UPLC-HRMS.
• Orthogonal partial least squares-discriminant analysis (oPLS-DA) for identifying discriminant metabolites.
• Development and validation of classification models using metabolite panels.

Main Results:

• Metabolite panels effectively discriminated NSCLC tumors from noncancerous tissues with high accuracy, sensitivity, and specificity.
• Specific metabolite panels were identified for adenocarcinoma (valine, sphingosine, glutamic acid γ-methyl ester, LPC (16:0)) and squamous cell carcinoma (valine, sphingosine, LPC (18:1), leucine derivatives).
• A five-metabolite panel (including valine and creatine) achieved 96.8% accuracy in discriminating between adenocarcinoma and squamous cell carcinoma, confirmed by external validation.

Conclusions:

• UPLC-HRMS-based metabolic profiling can accurately detect and subtype NSCLC.
• Identified discriminant metabolites offer potential biomarkers for NSCLC diagnosis and classification.
• The developed classification models demonstrate a promising prospect for clinical application in NSCLC management.