Precision medicine involves a personalized approach to healthcare acknowledging an individual-to-individual variability in genetics, environment, and lifestyle. Research in precision medicine can be pulled from basic, clinical or epidemiological sciences from which imaging, omics, or other types of data can be mined to contribute to the ‘information commons’ from which patient-specific patterns are drawn. Advancement in basic sciences that focus on imaging and other high content information processing for precision medicine is of particular importance in fields like oncology and nephrology where, diseases like focal segmented glomerular sclerosis have neither seen drug development in the past two decades, nor have an affirmative treatment plan. One reason is the lack of high-content high-throughput platforms for drug testing with a physiologically appropriate microenvironment.
This work aims to build a high-content platform for podocyte-based drug discovery. Having demonstrated that cells in patterns demonstrate a phenotypic change representative of the in vivo condition, we first start by building a robust 96-well plate with our microfabricated platform as its base. We demonstrate a relevant increase in expression of podocyte specific proteins like synaptopodin in our patterned podocytes along with a decrease in cell-to-cell variability when compared with their unpatterned counterparts. Next, we demonstrate the use of our platform as a tool for drug discovery by showing that we achieve a reproducible actin-based dose response curve using human podocyte cell lines, something that has never been done to our knowledge. We see that our platform pushes immortalized podocytes towards cell cycle arrest at a much earlier timepoint during differentiation with improved functional performance metrics, such as lower motility and increased cytoskeletal segregation. We show that our platform may be able to extend its versatility by synergizing the effects of substrate shape and stiffness, and we show a potential application in studying the effect of this platform on the expression of Yes associated protein (YAP).
We demonstrate the flexibility of this platform using another case study, this time with cancer cells. It is well known that the progression of neoplastic cells to metastasis is a major contributing factor to poor prognosis. The metastatic cascade involves invasion and migration coupled by angiogenesis and intravasation. The subsequent cells that survive circulation and attach to the endothelium extravasate and colonize in a distal location. Current techniques, such as Transwell and scratch assays that attempt to quantify metastatic potential are difficult to scale and consequently may be challenging to use in large-scale drug testing. We show that using our platform, we are able to rapidly quantify the metastatic potential of cancer cells in situ with high sensitivity, independent of cell seeding density. By changing the dimensions of our microfabricated patterns, we are able to vary the mechanical resistance that the cell experiences traversing and use this to mimic cell invasion across different microenvironments. Importantly, we show that we can quantify the effect of the metastatic potential in response to a pharmacological intervention and thus demonstrate that we can use this platform for drug testing.
In conclusion, we present a novel multifaceted platform and demonstrate its versatility with two different applications. In the context of drug discovery, we show that the platform serves as a superior model for podocyte injury. The reproducible Puromycin aminonucleocide (PAN) actin-based dose response curves obtained using this platform, opens avenues to investigate the effect of various targeted therapies for podocyte-based kidney diseases. In the context of screening for metastatic potential of cancer cells, we show that our platform exhibits a superior sensitivity to existing screening techniques. Additionally, the potential of using a patient’s own cells in the future for either application presents exciting avenues for precision medicine.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/49h3-3w20 |
| Date | January 2023 |
| Creators | Bhattacharya, Smiti |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
Page generated in 0.0024 seconds