# Metabolic permissiveness: how tissue context shapes cancer

## TL;DR

This paper explores how the tissue environment influences cancer cell metabolism, offering a framework to understand how cancer cells adapt differently based on their surroundings.

## Contribution

The concept of 'metabolic permissiveness' is introduced as a framework to explain tissue-specific metabolic adaptations in cancer.

## Key findings

- Identical oncogenic mutations can lead to different metabolic outcomes depending on the tissue context.
- Baseline metabolic architecture and the tumor microenvironment determine whether mutations provide a selective advantage or cause metabolic crisis.

## Abstract

In this review, Moschandrea and Frezza discuss the tissue-specific metabolic outcomes of canonical oncogene activation, aberrant tumor suppressor function, or mutated TCA cycle genes. Together with tissue-specific tumor microenvironments, they posit that the inherent metabolic permissiveness of a tissue environment shapes the metabolic adaptation of cancer cells and could have implications for precision medicine.

An emerging paradox in cancer metabolism is that identical oncogenic mutations produce profoundly different metabolic phenotypes depending on tissue context, with many mutations exhibiting striking tissue-restricted distributions. Here we introduce metabolic permissiveness as the inherent capacity of a tissue to tolerate, adapt to, or exploit metabolic disruptions, providing a unifying framework for explaining this selectivity. We examine tissue-specific metabolic rewiring driven by canonical oncogenes (MYC and KRAS), tumor suppressors (p53, PTEN, and LKB1), and tricarboxylic acid (TCA) cycle enzymes (FH, SDH, and IDH), demonstrating that baseline metabolic architecture, nutrient microenvironment, redox buffering, and compensatory pathways determine whether mutations confer a selective advantage or metabolic crisis. We further discuss how the tumor microenvironment shapes metabolic adaptation and therapeutic vulnerability. This framework reveals shared principles of tissue-specific metabolic vulnerability in cancer and provides a mechanistic basis for precision metabolic therapies.