Dataset Information

In vivo cell-cycle profiling in xenograft tumors by quantitative intravital microscopy.

ABSTRACT: Quantification of cell-cycle state at a single-cell level is essential to understand fundamental three-dimensional (3D) biological processes such as tissue development and cancer. Analysis of 3D in vivo images, however, is very challenging. Today's best practice, manual annotation of select image events, generates arbitrarily sampled data distributions, which are unsuitable for reliable mechanistic inferences. Here, we present an integrated workflow for quantitative in vivo cell-cycle profiling. It combines image analysis and machine learning methods for automated 3D segmentation and cell-cycle state identification of individual cell-nuclei with widely varying morphologies embedded in complex tumor environments. We applied our workflow to quantify cell-cycle effects of three antimitotic cancer drugs over 8 d in HT-1080 fibrosarcoma xenografts in living mice using a data set of 38,000 cells and compared the induced phenotypes. In contrast to results with 2D culture, observed mitotic arrest was relatively low, suggesting involvement of additional mechanisms in their antitumor effect in vivo.

SUBMITTER: Chittajallu DR

PROVIDER: S-EPMC4579269 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Publications

In vivo cell-cycle profiling in xenograft tumors by quantitative intravital microscopy.

Chittajallu Deepak R DR Florian Stefan S Kohler Rainer H RH Iwamoto Yoshiko Y Orth James D JD Weissleder Ralph R Danuser Gaudenz G Mitchison Timothy J TJ

Nature methods 20150413 6

Quantification of cell-cycle state at a single-cell level is essential to understand fundamental three-dimensional (3D) biological processes such as tissue development and cancer. Analysis of 3D in vivo images, however, is very challenging. Today's best practice, manual annotation of select image events, generates arbitrarily sampled data distributions, which are unsuitable for reliable mechanistic inferences. Here, we present an integrated workflow for quantitative in vivo cell-cycle profiling. ...[more]

PMID: 25867850

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Project description:Cellular communication constitutes a fundamental mechanism of life, for instance by permitting transfer of information through synapses in the nervous system and by leading to activation of cells during the course of immune responses. Monitoring cell-cell interactions within living adult organisms is crucial in order to draw conclusions on their behavior with respect to the fate of cells, tissues and organs. Until now, there is no technology available that enables dynamic imaging deep within the tissue of living adult organisms at sub-cellular resolution, i.e. detection at the level of few protein molecules. Here we present a novel approach called multi-beam striped-illumination which applies for the first time the principle and advantages of structured-illumination, spatial modulation of the excitation pattern, to laser-scanning-microscopy. We use this approach in two-photon-microscopy--the most adequate optical deep-tissue imaging-technique. As compared to standard two-photon-microscopy, it achieves significant contrast enhancement and up to 3-fold improved axial resolution (optical sectioning) while photobleaching, photodamage and acquisition speed are similar. Its imaging depth is comparable to multifocal two-photon-microscopy and only slightly less than in standard single-beam two-photon-microscopy. Precisely, our studies within mouse lymph nodes demonstrated 216% improved axial and 23% improved lateral resolutions at a depth of 80 µm below the surface. Thus, we are for the first time able to visualize the dynamic interactions between B cells and immune complex deposits on follicular dendritic cells within germinal centers (GCs) of live mice. These interactions play a decisive role in the process of clonal selection, leading to affinity maturation of the humoral immune response. This novel high-resolution intravital microscopy method has a huge potential for numerous applications in neurosciences, immunology, cancer research and developmental biology. Moreover, our striped-illumination approach is able to improve the resolution of any laser-scanning-microscope, including confocal microscopes, by simply choosing an appropriate detector.

Dataset Information

In vivo cell-cycle profiling in xenograft tumors by quantitative intravital microscopy.

Publications

In vivo cell-cycle profiling in xenograft tumors by quantitative intravital microscopy.

Similar Datasets

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