Cross-Scale Bioanalytical Integration for Decoding Tumour Regulatory Plasticity in Oncology.
Journal:
Critical reviews in oncology/hematology
Published Date:
Jun 30, 2026
Abstract
Cancer is characterized by extensive genetic variability, continuous evolutionary change, and intricate interactions with its surrounding microenvironment and causing substantial challenges for precise diagnosis, prognostic evaluationand therapeutic selection. Traditional bulk analytical methods fail to adequately resolve this complexity highlighting the need for advanced bioanalytical approaches that investigate tumor biology across spatial, temporal, and functional dimensions. The most recent advances in liquid biopsy technologies, single-cell and spatial omics, mass spectrometry based imaging, multi-layer proteomic and metabolomic profiling and AI-enabled computational analysis have transformed modern cancer research. This review highlights emerging integrated applications of bioanalytical technologies that help in high-resolution molecular profiling, maintain tissue architecture, and provide long-term time-based monitoring of disease dynamics. Single-cell transcriptomic and chromatin accessibility profiling identify cellular diversity and regulatory plasticity of cells, whereas spatial transcriptomics and multiplexed imaging map the spatial organisation of tumor-immune ecosystems. Complementary mass spectrometry-based, proteomic, and metabolomic approaches provide functional insights into signalling networks and metabolic adaptations. The increasing integration of these technologies through computational and artificial intelligence-driven frameworks further supports multi-omics convergence, biomarker identification, and predictive modelling. Looking ahead, key challenges include cross-scale data integration, dynamic disease tracking, and the development of clinically interpretable analytical tools. By integrating molecular resolution with spatial and temporal context, next-generation bioanalytical strategies are positioned to advance precision oncology, enabling earlier detection, adaptive therapeutic interventions, and personalised cancer management.
Authors
Keywords
No keywords available for this article.