# BRAF inhibitor resistance in melanoma: from resistance mechanisms to therapeutic innovations

## TL;DR

This paper reviews how melanoma becomes resistant to BRAF inhibitors and explores new therapies to overcome this resistance.

## Contribution

The paper provides a structured framework linking resistance mechanisms to targeted therapies in BRAF inhibitor-resistant melanoma.

## Key findings

- Resistance mechanisms include genetic, epigenetic, metabolic, and tumor microenvironment changes.
- Next-generation BRAFi, combination therapies, and RNA-based agents are proposed to combat resistance.
- Technologies like liquid biopsies and AI are highlighted for precision monitoring and treatment.

## Abstract

BRAF inhibitors (BRAFi) have transformed the treatment of BRAF mutant melanoma, but inherent and acquired resistance remains a major barrier to curative outcomes. Resistance arises from interconnected mechanisms: genetic alterations reactivating the MAPK pathway or bypass cascades (e.g., PI3K/AKT/RTK), epigenetic modulation, metabolic reprogramming, and the tumor microenvironment (TME) remodeling. Despite extensive research into these mechanisms, a cohesive framework linking each resistance module to targeted therapeutic strategies is lacking. This review systematically categorizes resistance into intrinsic and acquired subtypes: intrinsic resistance is driven by constitutive molecular traits of BRAF mutant melanoma (e.g., persistent MAPK activation, baseline PI3K/AKT hyperactivity), while acquired resistance emerges via therapeutic pressure-induced genetic mutations, epigenetic shifts, metabolic reprogramming, or TME modifications. For each identified resistance mechanism, we provide a detailed examination of corresponding therapeutic advancements. These encompass the development of next-generation BRAFi, strategically designed combination therapies, epigenetic modulators, immunotherapeutic approaches, and RNA-based therapeutic agents. Furthermore, we underscore the pivotal role of state-of-the-art technologies, such as liquid biopsies, single-cell multi-omics analyses, and artificial intelligence, in facilitating precise resistance monitoring and personalized therapy selection. By integrating these insights, we present a structured, translationally focused framework to guide basic research and clinical decision-making, ultimately advancing precision salvage therapy and trials aimed at preventing or overcoming BRAFi resistance.