Genome-scale metabolic modeling and machine learning unravel metabolic reprogramming and mast cell role in lung cancer through a multi-level analysis

Abstract

Lung cancer remains a leading cause of cancer-related deaths worldwide, with immune interactions, particularly involving mast cells, playing a crucial role. Mast cells contribute to both pro- and anti-tumorigenic activities, influencing immune modulation, angiogenesis, and tissue remodeling. This study provides a comprehensive multi-level analysis of metabolic alterations in lung cancer through genome-scale metabolic modeling (GSM) and machine learning. Using 43 paired lung tissue samples, we developed metabolic models of lung cancer and mast cells, revealing a significant reduction in resting mast cells in cancerous tissues. Our Random Forest classifier accurately distinguished between healthy and cancerous states, identifying key metabolic signatures. We found that lung cancer cells selectively upregulate valine, isoleucine, histidine, and lysine metabolism in the aminoacyl-tRNA pathway to support their elevated energy demands. Mast cell metabolism exhibited enhanced histamine transport and increased glutamine consumption in the tumor microenvironment, suggesting a shift towards immunosuppressive activity. Additionally, our novel Metabolic Thermodynamic Sensitivity Analysis (MTSA) showed impaired biomass production in cancerous mast cells across physiological temperatures (36 to 40C), indicating metabolic vulnerabilities. By elucidating the metabolic adaptations of mast cells and lung cancer cells, our study highlights their interplay in tumor progression and identifies potential therapeutic targets and diagnostic markers for future investigation. Author Summary: Our research examines the intricate relationship between lung cancer and mast cells, a type of immune cell, using advanced computational methods. We developed detailed metabolic models of lung tissue and mast cells through a multi-level approach to understand how their metabolism changes in cancer. Our findings reveal that lung cancer cells modify their metabolic pathways to meet increased energy demands, including enhanced utilization of four specific amino acids within the aminoacyl-tRNA pathway. In addition, mast cells in lung cancer environments show increased histamine release and glutamine consumption, suggesting they become more active in ways that might promote tumor growth. Additionally, we found that cancerous mast cells are less able to adapt to temperature changes compared to healthy ones, which could impact how they respond during fever or inflammation. These insights provide new perspectives on how lung cancer affects the immune system and could lead to novel approaches for diagnosis and treatment. By understanding these complex interactions, we aim to contribute to the development of more effective strategies for combating lung cancer.