Molecular profiling is increasingly explored in biology as a diagnostic, prognostic, and discerning tool. Gene and protein expression signatures generated using bioinformatics tools and databases are of predictive significance in identifying the phenotype or clinical status of a biological sample. This predictive bioinformatics approach finds application in a wide variety of disease conditions and tissue types. Identifying the hypoxic status of three-dimensional (3D) cultures is essential due to its divergent effects on cell survival. Though hypoxia limits the viable thickness of three-dimensional tissue engineering constructs, it also promotes angiogenesis into the construct, thereby facilitating its successful integration with the host tissue. Accurate determination of hypoxia in 3D cultures also finds use in tumour angiogenesis models. Efforts to generate hypoxic and angiogenic molecular signatures using computational databases (e.g., iHypoxia, AngioDB) and tools have proved fruitful. Exosomal molecular profiling is proposed as a non-invasive and real-time extrapolative tool to determine the hypoxic status within 3D cultures. Mathematical models can be created using R packages (e.g., randomForest and rpart) and exosomal databases (e.g., ExoCarta) to generate hypoxic decision tree classifiers to determine precisely the hypoxic status of discrete 3D culture samples. Hence, bioinformatics software and databases offer potent methodologies for non-invasive, high-throughput, real-time, in vitro monitoring of cellular states in tissue engineered constructs and 3D disease models.
Molecular profiling, Gene expression signatures, Exosomal miRNA profiling, Angiogenesis, 3D culture, Hypoxic status, Tissue engineering constructs, Decision tree classifiers
