Multilayer regulatory networks in cancer immunity: Systems-level insights through integrative omics

Cancer immunology has rapidly evolved with the growing recognition that the immune response to cancer is governed by complex, multilayered regulatory networks. Recent breakthroughs highlighted how immune cell dysfunction within the tumor microenvironment represents a critical barrier to the efficacy of immunotherapies. This dysfunction emerges not from isolated molecular aberrations, but from intricate crosstalk spanning epigenetic, transcriptional, post-transcriptional, and post-translational layers—collectively forming what can be termed the “cancer-immunity regulome.” Although high-throughput, multi-omics technologies now allow us to profile these layers with unprecedented resolution, a comprehensive understanding of how these regulatory mechanisms integrate and interact in shaping anti-cancer immunity remains incomplete. Current studies often focus on single layers or offer descriptive snapshots, underscoring the need for truly integrative, systems-level approaches to dissect this complexity and translate discoveries into new therapeutic strategies. combination strategies.This Research Topic aims to accelerate the use of integrative bioinformatics and systems biology to interrogate the regulatory logic driving tumor-related immune responses. We seek to assemble studies that not only generate predictive computational models of immune cell states and therapeutic outcomes, but also pinpoint master regulatory nodes as potential treatment targets. Our goal is to highlight innovations in algorithms, pipelines, and analytical frameworks that combine multi-omics data—including single-cell, epigenetic, and proteomic profiles—to build actionable models for the cancer-immunity interface. Further, we encourage contributions that close the discovery loop by experimentally validating computational findings, helping to reveal mechanisms, biomarkers, and opportunities for therapy modulation.We invite submissions that apply integrative analysis as a central methodology, with particular interest in approaches that bridge data, computation, and biological insight in cancer immunity. The scope of this Research Topic includes, but is not limited to:• Computational deconvolution of tumor-immune ecosystems to reveal novel cell states or regulatory circuits.• Multi-omic biomarker discovery for predicting immunotherapy response or resistance.• Construction and interpretation of context-specific regulatory networks for target discovery.• Development and validation of open-source computational tools, software, or databases for analyzing the cancer-immunity regulome.• Frameworks for experimental validation of computational predictions linking mechanism to function.Please note: Manuscripts consisting solely of bioinformatics or computational analysis of public genomic or transcriptomic databases which are not accompanied by validation (independent cohort or biological validation in vitro or in vivo) are out of scope for this section and will not be accepted as part of this Research Topic. Topic editors: Xu Chen, Yitao Qi, Ye Gong, Ming-xuan Liu, Zhongxiao Lin, Yuan Ma Source: https://www.frontiersin.org/research-topics/77033/multilayer-regulatory-networks-in-cancer-immunity-systems-level-insights-through-integrative-omics