A Landscape of Metabolic Variation across Tumor Types

Area of Science:

• Oncology
• Metabolomics
• Bioinformatics

Background:

• Tumor cells exhibit metabolic reprogramming to support rapid proliferation and overcome growth-related stress.
• While cancer-related enzyme alterations are widely studied, the role of small-molecule metabolites (substrates/products) remains less explored.

Purpose of the Study:

• To concurrently analyze metabolomics data across diverse cancer types.
• To identify common and heterogeneous metabolic alterations in tumors compared to normal tissues.
• To correlate metabolic profiles with clinical features and tumor aggressiveness.

Main Methods:

• Development of an informatic pipeline for integrated metabolomics analysis.
• Analysis of metabolomics data from over 900 tissue samples across seven cancer types.
• Joint analysis of metabolomic data with clinical patient features.

Main Results:

• Revealed extensive heterogeneity in cancer metabolic reprogramming across different tissue origins.
• Identified recurrently differentially abundant metabolites, including lactate and acyl-carnitine species, across multiple cancer types.
• Discovered specific metabolites, such as polyamines and kynurenine, associated with tumor aggressiveness.

Conclusions:

• Cancer metabolic reprogramming displays both common patterns and significant heterogeneity.
• Metabolite profiling offers insights into tumor biology and potential biomarkers for aggressive disease.
• The study provides a large-scale, web-accessible resource for cancer metabolomics research.