CaMeRe

CaMeRe infers cancer-specific metabolic pathways from gene expression data to identify metabolic reprogramming driven by altered intracellular concentrations of O₂, H₂O₂, and H⁺.

Key Features:

• Pathway Inference: Connects specified starting and ending compounds through collections of compatible enzymes guided by gene expression data from cancer tissue samples.
• Incorporation of Cancer-Specific Knowledge: Integrates cancer-specific information such as expression levels of bottleneck enzymes and intracellular concentrations of O₂, H₂O₂, and H⁺ to contextualize pathway inference.
• Application to Known Metabolic Phenomena: Predicts alterations in sugar-energy metabolism associated with the Warburg effect and reports appearance and ranking of key pathways in results.
• Efficiency and Scalability: Computational evaluations indicate the approach is fast and scalable for large-scale metabolic network inference tasks.

Scientific Applications:

• Analysis of metabolic reprogramming in cancer: Provides inferred pathways consistent with cancer tissue gene expression to study metabolic changes in tumors.
• Study of the Warburg effect: Identifies alterations in sugar-energy metabolism associated with the Warburg effect.
• Prioritization of therapeutic targets: Highlights bottleneck enzymes and ranked pathways to guide selection of metabolic intervention points.

Methodology:

Specify starting and ending compounds, identify collections of compatible enzymes that connect them, use gene expression data from cancer tissue samples and cancer-specific information (bottleneck enzyme expression and intracellular O₂, H₂O₂, H⁺ conditions) to select and rank coherent metabolic pathways.