Advances in high-throughput omics technologies are transforming our understanding of melanoma biology. Instead of focusing solely on individual genes or proteins, recent research reveals that melanoma is shaped by complex, dynamic signaling networks influenced by genetic, epigenetic, and environmental factors. Insights from genomics, transcriptomics, proteomics, and metabolomics, especially when integrated across multiple data types and scales, are opening new avenues for deciphering network-level disease mechanisms and developing personalized treatment strategies.

This Research Topic seeks to highlight studies that integrate multi-omics and systems-level approaches to unravel emergent signaling networks, drug response, and therapeutic resistance in melanoma. We particularly welcome work that:
• Integrates multi-dimensional omics datasets (e.g., genomics, epigenomics, transcriptomics, proteomics, metabolomics, and spatial/single-cell omics) to reconstruct and analyze melanoma signaling networks.
• Identifies and functionally characterizes novel pathways or regulatory networks informed by omics data.
• Uncovers mechanisms of drug sensitivity, immune evasion, and resistance through multi-omics integration.
• Investigates tumor-immune interactions or immune evasion using integrative omics approaches.
• Employs systems biology or computational network models (with experimental or clinical validation) to predict therapeutic outcomes or new intervention points.
• Utilizes spatial or single-cell omics to capture microenvironmental influences and signaling heterogeneity.
• Links omics-informed findings to patient response and clinical outcomes.
• Explores next-generation targeted or immune-based therapies and strategic combinations based on integrative signaling insights.

By distinctly centering on integrative, network-level, and high-dimensional omics approaches and inviting studies that go beyond single-gene or pathway-focused research, this collection aims to fill a gap not previously addressed by other melanoma Research Topics.

Please note: manuscripts consisting solely of bioinformatics, computational analysis, or predictions of public databases which are not accompanied by validation (independent clinical or patient cohort, or biological validation in vitro or in vivo, which are not based on public databases) are not suitable for publication in this journal.

Are you interested in contributing a manuscript to this Research Topic?

Melanoma Omics: Linking Emerging Signaling Pathways, Drug Response, and Novel Therapeutics