Design of an integrated microdevice to measure malignant lipid signaling in single cells from clinical samples

PROJECT SUMMARY / ABSTRACT Engineering advances applied to miniaturized analytical instrumentation will be employed to improve sensitivity and throughput of thin-layer chromatography enabling single-cell analyses of the biochemical activity of lipid modifying enzymes in the cells of patients. By utilizing micro- and nanofabrication techniques, the proposed work will develop a novel ultra-miniaturized device termed picoliter thin-layer chromatography (pTLC) suitable for assays at high throughput and sensitivity. A multidisciplinary collaboration encompassing bioengineering, chemistry and oncology will develop the pTLC chip and integrate its supporting hardware to create an easy-to-use instrument readily amenable to point-of-care applications in a clinical setting. Sample handling and analysis protocols will be developed to ensure system compatibility with common laboratory workflows. The improvements engendered by miniaturized chromatography and nanofabrication of silica gels in this lab-on-chip device will enable experiments that demonstrate the potential and power of the platform by assessing of the roles of specific enzyme targets in dynamic reprogramming underlying resistance to chemotherapy in patients with acute myeloid leukemia (AML). The technique will capitalize on recent synthetic lipid innovations to employ a large and growing list of commercially available, cell-loadable, fluorescent, and clickable lipid probes now available or in development. These probes will be used to simultaneously elucidate enzyme activity in the sphingolipid, phosphoinositide and fatty acid signaling pathways hypothesized to serve critical roles in developing resistance to targeted therapies. By simultaneously tracking multiple signaling pathways in individual patient cells, we will identify the strategies that AML cells use to dynamically reprogram their growth-promoting pathways during and after drug treatment. A powerful attribute of these measurements is their performance on single cells from patient samples avoiding the confounding aspects of averaged data yielded by bulk cell analysis and genetic drift in cell lines. This work will demonstrate that the pTLC platform can provide key information from which the best treatment option(s) may in the future be chosen for patients with various cancers and will contribute fundamental data in the emerging field of precision medicine.