My lab is researching the utility of real-time, live cell biomass profiling to address critical shortcomings in predicting therapeutic responses to anticipate tumor recurrence, which is usually based on tumor heterogeneity. This approach can non-invasively measure the cell mass in real-time of living cells. Those cells that are growing, gain mass, while those dying in response to a drug will lose mass. This technology is different than using metabolism-based proliferation assays or luciferase reporter-based quantification of cell viability because it provides data at an individual-cell level. This information is important because it may be helpful in identifying drug combinations that impact all cells, compared with other combinations that may clearly affect 80% of cells, but have no impact on the remaining 20%. Another focus area for my lab is the use of high-speed atomic force microscopy (HSAFM) as a rapid, low cost method to quantify nucleic acid abundance in minute samples. Detection of and counting the copy number of a particular species of DNA molecule in a heterogeneous mixture of relatively small sample quantity, such as might be derived from a tissue biopsy, occupies a central role in many biotechnology applications (e.g. transcription profiling, exome sequencing, polymorphism detection, RNA seq, chromatin immunoprecipitation seq, and so on). In these applications, detection methods require very high signal-to-noise ratios and the ability to yield a signal from small numbers (<100) of positive events. Over the last decades, these applications have been addressed by PCR, in situ hybridization of species-specific fluorescent oligos, microarrays and next-generation sequencing, but not without certain shortfalls and shortcomings. Chief among these limitations is their relative insensitivity, requiring enzymatic amplification of low-abundance samples. Nanotechnology-based single molecule approaches we are developing provide a competing approach to such applications requiring molecular recognition, thus opening new avenues to medical diagnostics, genetic tests, and pathogen detection.
Animal models,Autophagy,Bioinformatics,Biomarkers,Cancer diagnostics,Cancer disparities,Cancer therapy resistance,Drug discovery,Genomics,Precision medicine,Senescence,Targeted therapies