Cellular Heterogeneity and Intercellular Communication in the Tumor Microenvironment: Integrative Multi-Omics and Computational Approaches

The tumor microenvironment (TME) is a complex ecosystem in which malignant cells, immune populations, stromal components, and endothelial cells interact dynamically to shape disease progression, therapeutic response, and clinical outcomes. Disentangling these interactions at scale -across cancer types and patient cohorts- demands computational approaches that go beyond aggregate tissue-level measurements and instead leverage the cellular heterogeneity embedded within bulk and spatially-resolved omics data.This Research Topic invites contributions at the intersection of computational oncology, systems biology, and multi-omics integration, with a focus on two complementary challenges: (1) cell-type aware predictive modeling of disease phenotypes, including survival, drug response, tumor grade, and immune evasion; and (2) network-based modeling of intercellular communication, capturing ligand–receptor signaling, transcriptional co-regulation, and spatially-constrained cell–cell crosstalk.We welcome original research articles, methods papers, and reviews addressing -but not limited to- the following themes:- Deconvolution and cell-type proportion estimation from bulk RNA-seq, proteomics, or DNA methylation data, and their integration into phenotype prediction frameworks- Machine learning and deep learning models that incorporate cell-type composition or cell-type-specific gene expression as predictive features for clinical or molecular phenotypes- Construction and analysis of intercellular signaling networks using inferred or measured cell-type-resolved omics, including ligand–receptor interaction databases and graph-based modeling approaches- Spatial transcriptomics and multi-modal spatial omics for mapping cell–cell communication in situ, including spatially-aware deconvolution and neighborhood-level interaction modeling- Pan-cancer or cross-cohort analyses that generalize cell-type aware models across tumor types or datasets- Computational benchmarking, validation frameworks, and tools that assess robustness and biological interpretability of cell-type aware predictions- Integration of single-cell reference atlases with bulk or spatial cohort data to enable cell-type resolved inference at population scale- Translational applications: biomarker discovery, patient stratification, and identification of therapeutic vulnerabilities through the lens of intercellular networksPlease 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 Research Topic. Topic editors: Shrabanti Chowdhury, Anchal Ghai, Jing Ma Source: https://www.frontiersin.org/research-topics/82259/cellular-heterogeneity-and-intercellular-communication-in-the-tumor-microenvironment-integrative-multi-omics-and-computational-approaches