# Comprehensive proteome profiling of cytochrome P450 isoforms in cancer models

## TL;DR

This study maps CYP450 enzyme expression in various cancers, revealing differences that could help improve drug treatments and reduce side effects.

## Contribution

The first semi-quantitative proteomic map of CYP450 isoforms across multiple cancer models is presented.

## Key findings

- CRC models showed high expression of CYP2W1 and CYP2S1.
- HNSCC models exhibited prominent CYP1B1 and CYP2W1 expression.
- Hepatic cancer models were enriched in CYP3A and CYP2C subfamily members.

## Abstract

Cytochrome P450 (CYP450) enzymes are essential for drug metabolism, xenobiotic detoxification, and procarcinogen activation, playing a pivotal role in both normal physiology and cancer biology. Their expression varies significantly across tissues and tumour types, reflecting the metabolic heterogeneity of cancers. Understanding these variations is critical for developing targeted therapies, optimizing drug efficacy, and minimizing toxicity. This study aimed to comprehensively profile CYP450 expression across colorectal cancer (CRC), head and neck squamous cell carcinoma (HNSCC), breast cancer, and hepatic cancer models using proteomic techniques.

We analysed various cancer models (cell lines, xenografts, and patient tissue biopsies) using gel electrophoresis coupled with liquid chromatography-mass spectrometry (GEL-LC-MS). Equal amounts of protein were separated by gel electrophoresis, and the 45-65 kDa molecular weight range was analysed on the Orbitrap Fusion Mass Spectrometer.

Distinct CYP450 expression profiles were observed across cancer types. In CRC, CYP2W1 and CYP2S1 were highly expressed, while CYP1B1 and CYP2W1 were prominent in HNSCC, highlighting their potential as biomarkers and therapeutic targets. Breast cancer models predominantly expressed CYP2J2 and CYP2S1, whereas CYP3A and CYP2C subfamily members were enriched in hepatic cancer, underscoring their roles in xenobiotic metabolism and drug clearance.

This study provides the first comprehensive semi-quantitative proteomic map of CYP450 isoforms across multiple cancer models. The findings reveal metabolic heterogeneity and identify clinically relevant targets, offering a foundation for future functional studies and personalized therapeutic strategies.