# Multi-omics integration in deciphering non-small cell lung cancer drug resistance: current status, challenges, and future prospects

## TL;DR

This paper reviews how combining different types of biological data helps understand and overcome drug resistance in non-small cell lung cancer.

## Contribution

The paper highlights novel strategies using multi-omics integration to identify drug resistance mechanisms and potential therapeutic targets in NSCLC.

## Key findings

- Multi-omics integration reveals molecular networks and key biomarkers of drug resistance in NSCLC.
- Small-molecule inhibitors and combination therapies guided by multi-omics data can reverse resistance.
- Future efforts should focus on AI-driven analysis and personalized medicine based on multi-omics data.

## Abstract

Lung cancer is the leading cause of cancer-related deaths globally. Non-small cell lung cancer (NSCLC) accounts for approximately 85% of all lung cancer cases, and drug resistance severely undermines treatment efficacy. This review summarizes recent advances in elucidating NSCLC drug-resistance mechanisms using multi-omics integration. Multi-omics integration systematically reveals the molecular networks of drug resistance, identifies key biomarkers and targets, and facilitates the screening of high-priority candidates for drug development through experimental validation. Small-molecule inhibitors targeting drug-resistant proteins and multi-omics-guided combination therapies offer strategies to reverse resistance. Future directions involve developing simultaneous multi-omics detection technologies, leveraging artificial intelligence for intelligent data analysis, establishing standardized frameworks for data sharing, and implementing personalized medicine based on multi-omics to improve patient prognosis.