Decoding the tumor immune microenvironment through multi-omics and signaling pathway analysis in cancer

The field of cancer immunology has witnessed dramatic progress with the advent of immunotherapies targeting the tumor immune microenvironment (TIME). Despite these advancements, the variable patient response to immunotherapeutic interventions such as immune checkpoint inhibitors continues to be a central challenge. Recent explorations using multi-omics technologies—spanning genomics, transcriptomics, proteomics, metabolomics, and spatial transcriptomics—have begun to enumerate the intricate cellular states and regulatory circuits operating within the TIME. Key studies have revealed diverse immune cell phenotypes, dynamic signaling pathways, and metabolic adaptations that can influence immune escape and therapeutic resistance. However, comprehensive integration of these data layers to generate actionable insights, particularly those that can be readily translated into prognostic markers or therapeutic strategies, remains an unmet need. There are ongoing debates about the dominant immune-evasive pathways and methodological hurdles in harmonizing multi-modal datasets, underlining the necessity for deeper functional validation and clinically relevant discoveries.

This Research Topic aims to consolidate pioneering work that utilizes multi-omics methodologies to unravel the mechanisms underpinning immune regulation and evasion within cancers. The objective is to foster research that not only characterizes the diverse cellular and molecular components of the TIME, but also elucidates the key signaling axes—such as interferon, JAK-STAT, NF-κB, Wnt/β-catenin, and TGF-β—that dictate immunotherapy responses. We seek to highlight studies employing integrative approaches, single-cell and spatial profiling, and functional assays that clarify the roles of these pathways in shaping tumor immunity and immunotherapeutic outcomes. By supporting contributions that leverage both computational and experimental tools, we aim to drive interdisciplinary discussions and accelerate the translation of multi-omics findings into clinically actionable biomarker panels and targeted therapy strategies for personalized immuno-oncology.

This Research Topic will focus on research that innovatively dissects the TIME using multi-omics data and functionally validates key regulatory networks influencing cancer immunity and immunotherapy. To gather further insights in the boundaries of multi-omics-driven exploration of the TIME and regulatory pathways, we welcome articles addressing, but not limited to, the following themes:

• Multi-omics integration for TIME stratification and biomarker discovery
• Single-cell and spatial omics approaches in mapping immune and stromal cell states and spatial interactions
• Elucidation of signaling pathways mediating immune exclusion, dysfunction, and immunosuppression
• Metabolic crosstalk between tumor and immune cells impacting immunotherapy efficacy
• Computational and AI-based models for TIME deconvolution and pathway inference
• Functional validation of candidate biomarkers and therapeutic targets
• Clinical translation of multi-omics signatures for predicting or monitoring immunotherapy responses

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.