Quantification of long-term doxorubicin response dynamics in breast cancer cell lines to direct treatment schedules.

While acquired chemoresistance is recognized as a key challenge to treating many types of cancer, the dynamics with which drug sensitivity changes after exposure are poorly characterized. Most chemotherapeutic regimens call for repeated dosing at regular intervals, and if drug sensitivity changes on a similar time scale then the treatment interval could be optimized to improve treatment performance. Theoretical work suggests that such optimal schedules exist, but experimental confirmation has been obstructed by the difficulty of deconvolving the simultaneous processes of death, adaptation, and regrowth taking place in cancer cell populations. Here we present a method of optimizing drug schedules in vitro through iterative application of experimentally calibrated models, and demonstrate its ability to characterize dynamic changes in sensitivity to the chemotherapeutic doxorubicin in three breast cancer cell lines subjected to treatment schedules varying in concentration, interval between pulse treatments, and number of sequential pulse treatments. Cell populations are monitored longitudinally through automated imaging for 600-800 hours, and this data is used to calibrate a family of cancer growth models, each consisting of a system of ordinary differential equations, derived from the bi-exponential model which characterizes resistant and sensitive subpopulations. We identify a model incorporating both a period of growth arrest in surviving cells and a delay in the death of chemosensitive cells which outperforms the original bi-exponential growth model in Akaike Information Criterion based model selection, and use the calibrated model to quantify the performance of each drug schedule. We find that the inter-treatment interval is a key variable in determining the performance of sequential dosing schedules and identify an optimal retreatment time for each cell line which extends regrowth time by 40%-239%, demonstrating that the time scale of changes in chemosensitivity following doxorubicin exposure allows optimization of drug scheduling by varying this inter-treatment interval.

Computational identification of surface markers for isolating distinct subpopulations from heterogeneous cancer cell populations.

Intratumor heterogeneity reduces treatment efficacy and complicates our understanding of tumor progression. There is a pressing need to understand the functions of heterogeneous tumor cell subpopulations within a tumor, yet biological systems to study these processes in vitro are limited. With the advent of single-cell RNA sequencing (scRNA-seq), it has become clear that some cancer cell line models include distinct subpopulations. Heterogeneous cell lines offer a unique opportunity to study the dynamics and evolution of genetically similar cancer cell subpopulations in controlled experimental settings. Here, we present clusterCleaver, a computational package that uses metrics of statistical distance to identify candidate surface markers maximally unique to transcriptomic subpopulations in scRNA-seq which may be used for FACS isolation. clusterCleaver was experimentally validated using the MDA-MB-231 and MDA-MB-436 breast cancer cell lines. ESAM and BST2/tetherin were experimentally confirmed as surface markers which identify and separate major transcriptomic subpopulations within MDA-MB-231 and MDA-MB-436 cells, respectively. clusterCleaver is a computationally efficient and experimentally validated workflow for identification and enrichment of distinct subpopulations within cell lines which paves the way for studies on the coexistence of cancer cell subpopulations in well-defined in vitro systems.

Quantitative analysis of the Oculus Rift S in controlled movement.

PURPOSE: To assess the translational and rotational tracking performance of the Oculus Rift S using controlled robotic motion and a gold-standard motion tracking system. MATERIALS AND METHODS: An Oculus Rift S headset and controller were each placed in an industrial robot arm and had Vicon passive markers placed on them. The robotic arm was then translated in three perpendicular directions and performed three orthogonal rotations about three orthogonal axes while the spatial position of the headset and controller were recorded by Vicon motion capture cameras as well as Unity. Positional data was analyzed to determine the difference in tracking between Unity and Vicon to establish the accuracy of the Rift S' tracking capabilities. RESULTS: It was determined that the translational accuracy of the system was 1.66 ± 0.74 mm for the head-mounted display and 4.36 ± 2.91 mm for the controller, and the rotational accuracy of the system was 0.34 ± 0.38° for the HMD and 1.13 ± 1.23° for the controller. CONCLUSIONS: The high level of accuracy and precision combined with the low cost of the Oculus Rift S and its use of inside-out tracking make it a viable candidate for clinicians looking to incorporate virtual reality.Implications for RehabilitationThe Oculus Rift S can report the position and orientation of the user's headmounted display and controllers during gameplay.The Oculus Rift S provides a more portable VR system which does not require external sensors to track motion, allowing it to be used in a variety of rehabilitation scenarios while still providing adequate motion tracking.

Applications of high-resolution clone tracking technologies in cancer.

Tumors are comprised of dynamic, heterogenous cell populations characterized by numerous genetic and non-genetic alterations that accumulate and change with disease progression and treatment. Retrospective analyses of tumor evolution have relied on the measurement of genetic markers (such as copy number variants) to infer clonal dynamics. However, these approaches neglect the critical contributions of non-genetic drivers of disease. Techniques that harness the power of prospective clone tracking via heritable barcode tags provide an alternative strategy. In this review, we discuss methods for high-resolution, quantitative clone tracking, including recent advancements to pair barcode-specific functionality with scRNA-seq, clonal cell isolation, and in situ hybridization and imaging. We discuss these approaches in the context of cancer cell heterogeneity and treatment resistance.

A quantitative method for evaluation of 6 degree of freedom virtual reality systems.

Modern virtual reality systems such as the HTC Vive enable users to be immersed in a virtual world. Validation of the HTC Vive and other contemporaneous systems for use in clinic, research, and industry applications will assure users and developers that games and applications made for these systems are accurate representations of the real world. The purpose of this study was to develop a standardized method for testing the translational and rotational capabilities of VR systems such as the HTC Vive. The translational and rotational capabilities of the HTC Vive were investigated using an industry grade robot arm and a gold standard motion capture system. It was found that the average difference between reported translational distances traveled was 0.74 ±â€¯0.42 mm for all room-scale calibration trials and 0.63 ±â€¯0.27 mm for all standing calibration trials. The mean difference in angle rotated was 0.46 ±â€¯0.46° for all room-scale calibration trials and 0.66 ±â€¯0.40° for all standing calibration trials. When tested using human movement, the average difference in distance traveled was 3.97 ±â€¯3.37 mm. Overall, the HTC Vive shows promise as a tool for clinic, research, and industry and its controllers can be accurately tracked in a variety of situations. The methodology used for this study can easily be replicated for other VR systems so that direct comparisons can be made as new systems become available.