Person:

Giedt, Randy

Recent advances in the field of intravital imaging have for the first time allowed us to conduct pharmacokinetic and pharmacodynamic studies at the single cell level in live animal models. Due to these advances, there is now a critical need for automated analysis of pharmacokinetic data. To address this, we began by surveying common thresholding methods to determine which would be most appropriate for identifying fluorescently labeled drugs in intravital imaging. We then developed a segmentation algorithm that allows semi-automated analysis of pharmacokinetic data at the single cell level. Ultimately, we were able to show that drug concentrations can indeed be extracted from serial intravital imaging in an automated fashion. We believe that the application of this algorithm will be of value to the analysis of intravital microscopy imaging particularly when imaging drug action at the single cell level.

Intravital microscopy is increasingly used to visualize and quantitate dynamic biological processes at the (sub)cellular level in live animals. By visualizing tissues through imaging windows, individual cells (e.g., cancer, host, or stem cells) can be tracked and studied over a time-span of days to months. Several imaging windows have been developed to access tissues including the brain, superficial fascia, mammary glands, liver, kidney, pancreas, and small intestine among others. Here, we review the development of imaging windows and compare the most commonly used long-term imaging windows for cancer biology: the cranial imaging window, the dorsal skin fold chamber, the mammary imaging window, and the abdominal imaging window. Moreover, we provide technical details, considerations, and trouble-shooting tips on the surgical procedures and microscopy setups for each imaging window and explain different strategies to assure imaging of the same area over multiple imaging sessions. This review aims to be a useful resource for establishing the long-term intravital imaging procedure.

Mitochondria, which are essential organelles in resting and replicating cells, can vary in number, mass and shape. Past research has primarily focused on short-term molecular mechanisms underlying fission/fusion. Less is known about longer-term mitochondrial behavior such as the overall makeup of cell populations’ morphological patterns and whether these patterns can be used as biomarkers of drug response in human cells. We developed an image-based analytical technique to phenotype mitochondrial morphology in different cancers, including cancer cell lines and patient-derived cancer cells. We demonstrate that (i) cancer cells of different origins, including patient-derived xenografts, express highly diverse mitochondrial phenotypes; (ii) a given phenotype is characteristic of a cell population and fairly constant over time; (iii) mitochondrial patterns correlate with cell metabolic measurements and (iv) therapeutic interventions can alter mitochondrial phenotypes in drug-sensitive cancers as measured in pre- versus post-treatment fine needle aspirates in mice. These observations shed light on the role of mitochondrial dynamics in the biology and drug response of cancer cells. On the basis of these findings, we propose that image-based mitochondrial phenotyping can provide biomarkers for assessing cancer phenotype and drug response.

Molecular profiling of central nervous system lymphomas in cerebrospinal fluid (CSF) samples can be challenging due to the paucicellular and limited nature of the samples. Presented herein is a microfluidic platform for complete CSF lymphoid cell analysis, including single cell capture in sub-nanoliter traps, and molecular and chemotherapeutic response profiling via on-chip imaging, all in less than one hour. The system can detect scant lymphoma cells and quantitate their kappa/lambda immunoglobulin light chain restriction patterns. The approach can be further customized for measurement of additional biomarkers, such as those for differential diagnosis of lymphoma subtypes or for prognosis, as well as for imaging exposure to experimental drugs.

Targeting DNA repair pathways is a powerful strategy to treat cancers. To gauge efficacy in vivo, typical response markers include late stage effects such as tumor shrinkage, progression free survival, or invasive repeat biopsies. These approaches are often difficult to answer critical questions such as how a given drug affects single cell populations as a function of dose and time, distance from microvessels or how drug concentration (pharmacokinetics) correlates with DNA damage (pharmacodynamics). Here, we established a single-cell in vivo pharmacodynamic imaging read-out based on a truncated 53BP1 double-strand break reporter to determine whether or not poly(ADP-ribose) polymerase (PARP) inhibitor treatment leads to accumulation of DNA damage. Using this reporter, we show that not all PARP inhibitor treated tumors incur an increase in DNA damage. The method provides a framework for single cell analysis of cancer therapeutics in vivo.