Decoding Cancer Invasion: Adhesion, Migration, and the Emergence of Actionable Biomarkers in the Era of Artificial Intelligence and Machine Learning

Cancer invasion, metastasis, and therapy resistance remain the principal obstacles to durable cancer control. These processes are driven by dynamic and reversible alterations in cell-cell and cell-matrix adhesion, reprogramming of migratory and invasive behaviors, and sustained crosstalk with the tumor microenvironment. Collectively, these biological programs enable tumor plasticity, support survival under therapeutic pressure, and facilitate disease progression across cancer types.Importantly, invasion biology leaves identifiable molecular, spatial, and histopathologic imprints in patient tissues and model systems. Advances in molecular profiling, spatial transcriptomics, and single-cell technologies, as well as artificial intelligence (AI), machine learning (ML), and integrative digital pathology now allow these imprints to be decoded and translated into actionable diagnostic, prognostic, and predictive biomarkers.This Research Topic aims to bring together interdisciplinary contributions at the intersection of cancer cell adhesion and migration, invasion-associated plasticity, tumor–microenvironment interactions, molecular and genetic pathology, and AI/ML within the framework of precision oncology. We welcome studies that dissect the cellular and molecular mechanisms governing invasion, as well as work that connects these mechanisms to clinically relevant tissue-based and molecular readouts.Topics of interest include, but are not limited to:(i) Adhesion-, cytoskeleton-, and mechanotransduction-linked signaling pathways that regulate invasion and metastatic spread;(ii) Epithelial-to-mesenchymal transition (EMT), partial EMT, collective migration, and other adaptive plasticity states that promote persistence, dissemination, and relapse;(iii) Extracellular matrix remodeling and microenvironmental drivers of invasion, including stromal, immune, vascular, and perineural niches;(iv) Tissue and molecular biomarkers of aggressive behavior and treatment resistance, encompassing immunohistochemistry and multiplex imaging, genomic and transcriptomic signatures, spatial profiling, single-cell analyses, and integrated multi-omics approaches; and(v) Translational experimental models that capture invasive dynamics and therapeutic response, including 3D culture systems, organoids and spheroids, co-culture platforms, and patient-derived models.The scope of this Research Topic is intentionally broad across tumor types to encourage cross-disciplinary exchange and facilitate cross-listing across complementary Frontiers sections. Article types may include Original Research, Methods, Reviews, Mini-Reviews, Perspectives, and Hypothesis & Theory papers. Topic editors: Hisham F. Bahmad, Wassim Abou-Kheir Source: https://www.frontiersin.org/research-topics/77769/decoding-cancer-invasion-adhesion-migration-and-the-emergence-of-actionable-biomarkers-in-the-era-of-artificial-intelligence-and-machine-learning