Nuclear mechanopathology and early cancer diagnostics: implications to radiation therapy
We recently showed that nuclear morphometrics and chromatin condensation patterns, obtained using single-cell imaging combined with machine learning methods, provide robust biomarkers to classify normal and cancerous disease states. To refine these methods further, we will implement confocal light microscopy techniques, including super-resolution capabilities, and integrate these methods with X-ray microscopy techniques. Such correlative imaging methods, combined with functional genomics, will provide novel methods to analyse the mechanical control of in situ chromatin architecture during cancer progression and for early cancer diagnostics. In the next phase, we will apply our diagnostic platform to interrogate the impact of radiation therapy on tumour microenvironment. Radiation therapies, either using radiolabelled chemicals or direct beam radiation such as Proton therapy, have emerged as important approaches to ablate diseased tissues in human patients, although the underlying nuclear and chromatin related mechanisms are unclear. Towards this end, we will also develop portable microfluidic devices and gene expression methods combined with machine learning to analyse both cell culture based stromal tissue organoid models and liquid and tissue biopsies obtained from patients undergoing various radiation therapies and to detect relapse conditions.