# Cancer Metabolism and Its Historical & Molecular Foundations: An Overview

## TL;DR

This paper reviews how cancer cells rewire their metabolism to support tumor growth and suggests new strategies for targeting these changes.

## Contribution

The paper introduces a unifying framework for cancer metabolism involving metabolic plasticity, oncometabolite-driven epigenetic remodeling, and immune-metabolic crosstalk.

## Key findings

- Cancer metabolism involves more than glycolysis, including glutamine metabolism and lipid synthesis.
- Metabolic reprogramming is driven by oncogenes, tumor suppressor genes, and the tumor microenvironment.
- Emerging strategies like metabolic inhibitors and immuno-metabolic combinations show promise for precision cancer treatment.

## Abstract

Cancer metabolism is a cornerstone of tumor biology, characterized by profound alterations in cellular energy production and biosynthetic pathways that drive malignancy. The seminal discovery of the “Warburg effect”, the preference of cancer cells for aerobic glycolysis even under oxygen-rich conditions, provided the first major insight into this field. Historically, this observation was attributed to defective mitochondria, but modern research has revealed a far more complex picture of metabolic reprogramming that is actively driven by oncogenes, tumor suppressor genes, and the tumor microenvironment (TME). This review advances a unifying framework for understanding cancer metabolism as a dynamic ecosystem defined by three interconnected adaptations: metabolic plasticity, oncometabolite-driven epigenetic remodeling, and immune-metabolic crosstalk. These adaptations extend beyond glycolysis to encompass glutamine metabolism, lipid synthesis, amino acid utilization, and mitochondrial dynamics, all coordinated to fuel rapid proliferation, promote survival, and enable metastasis. By examining the drivers, consequences, and therapeutic barriers within this framework, we highlight emerging strategies for precision intervention. Although understanding the mechanistic basis of these pathways has unveiled new therapeutic avenues, clinical translation has been limited by metabolic redundancy, microenvironmental buffering, and patient heterogeneity. Strategies such as metabolic inhibitors, dietary interventions, and immuno-metabolic combinations offer promising prospects for disrupting tumor growth when guided by biomarker-driven patient selection and emerging technologies, including spatial metabolomics and AI-driven network modeling.