Christina Mark, Natalie S Callander, Kenny Chng, Shigeki Miyamoto, Jay Warrick
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引用次数: 0
Abstract
Heterogeneity among cancer cells and in the tumor microenvironment (TME) is thought to be a significant contributor to the heterogeneity of clinical therapy response observed between patients and can evolve over time. A primary example of this is multiple myeloma (MM), a generally incurable cancer where such heterogeneity contributes to the persistent evolution of drug resistance. However, there is a paucity of functional assays for studying this heterogeneity in patient samples or for assessing the influence of the patient TME on therapy response. Indeed, the population-averaged data provided by traditional drug response assays and the large number of cells required for screening remain significant hurdles to advancement. To address these hurdles, we developed a suite of accessible technologies for quantifying functional drug response to a panel of therapies in ex vivo three-dimensional culture using small quantities of a patient's own cancer and TME components. This suite includes tools for label-free single-cell identification and quantification of both cell division and death events with a standard brightfield microscope, an open-source software package for objective image analysis and feasible data management of multi-day timelapse experiments, and a new approach to fluorescent detection of cell death that is compatible with long-term imaging of primary cells. These new tools and capabilities are used to enable sensitive, objective, functional characterization of primary MM cell therapy response in the presence of TME components, laying the foundation for future studies and efforts to enable predictive assessment drug efficacy for individual patients.
期刊介绍:
Integrative Biology publishes original biological research based on innovative experimental and theoretical methodologies that answer biological questions. The journal is multi- and inter-disciplinary, calling upon expertise and technologies from the physical sciences, engineering, computation, imaging, and mathematics to address critical questions in biological systems.
Research using experimental or computational quantitative technologies to characterise biological systems at the molecular, cellular, tissue and population levels is welcomed. Of particular interest are submissions contributing to quantitative understanding of how component properties at one level in the dimensional scale (nano to micro) determine system behaviour at a higher level of complexity.
Studies of synthetic systems, whether used to elucidate fundamental principles of biological function or as the basis for novel applications are also of interest.