Integrating necroptosis into pan-cancer immunotherapy: a new era of personalized treatment

Abstract

Introduction: Necroptosis has emerged as a promising biomarker for predicting immunotherapy responses across various cancer types. Its role in modulating immune activation and therapeutic outcomes offers potential for precision oncology.

Methods: A comprehensive pan-cancer analysis was performed using bulk RNA sequencing data to develop a necroptosis-related gene signature, termed Necroptosis.Sig. Multi-omics approaches were employed to identify critical pathways and key regulators of necroptosis, including HMGB1. Functional validation experiments were conducted in A549 lung cancer cells to evaluate the effects of HMGB1 knockdown on tumor proliferation and malignancy.

Results: The Necroptosis.Sig gene signature effectively predicted responses to immune checkpoint inhibitors (ICIs). Multi-omics analyses highlighted HMGB1 as a key modulator of necroptosis, with potential to enhance immune activation and therapeutic efficacy. Functional experiments demonstrated that HMGB1 knockdown significantly suppressed tumor proliferation and malignancy, reinforcing the therapeutic potential of targeting necroptosis.

Discussion: These findings underscore the utility of necroptosis as a biomarker to guide personalized immunotherapy strategies. By advancing precision oncology, necroptosis provides a novel avenue for improving cancer treatment outcomes.

Keywords: immune microenvironment; immunotherapy; machine learning; necroptosis; pan-cancer analysis.