Evaluating the Accuracy of FUCCI Cell Cycle In Vivo Fluorescent Imaging to Assess Tumor Proliferation in Preclinical Oncology Models

Yun, Lingsong; Massicano, Adriana V F; Gallegos, Carlos Andres; Heinzman, Katherine; Parish, Sean W.; Warram, Jason M.; Sorace, Anna G.

doi:10.1007/s11307-022-01739-9

Cited by 3 publications

(4 citation statements)

References 45 publications

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“…IF staining was performed as described [21]. Briefly, paraffin-embedded tumors were sectioned as 5 μm slides and dewaxed with xylene.…”

Section: Immunofluorescence (If) Stainingmentioning

confidence: 99%

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Evaluating the immunologically “cold” tumor microenvironment after treatment with immune checkpoint inhibitors utilizing PET imaging of CD4 + and CD8 + T cells in breast cancer mouse models

Lu,

Houson,

Gallegos

et al. 2024

Breast Cancer Res

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Background Immune-positron emission tomography (PET) imaging with tracers that target CD8 and granzyme B has shown promise in predicting the therapeutic response following immune checkpoint blockade (ICB) in immunologically “hot” tumors. However, immune dynamics in the low T-cell infiltrating “cold” tumor immune microenvironment during ICB remain poorly understood. This study uses molecular imaging to evaluate changes in CD4 + T cells and CD8 + T cells during ICB in breast cancer models and examines biomarkers of response. Methods [89Zr]Zr-DFO-CD4 and [89Zr]Zr-DFO-CD8 radiotracers were used to quantify changes in intratumoral and splenic CD4 T cells and CD8 T cells in response to ICB treatment in 4T1 and MMTV-HER2 mouse models, which represent immunologically “cold” tumors. A correlation between PET quantification metrics and long-term anti-tumor response was observed. Further biological validation was obtained by autoradiography and immunofluorescence. Results Following ICB treatment, an increase in the CD8-specific PET signal was observed within 6 days, and an increase in the CD4-specific PET signal was observed within 2 days in tumors that eventually responded to immunotherapy, while no significant differences in CD4 or CD8 were found at the baseline of treatment that differentiated responders from nonresponders. Furthermore, mice whose tumors responded to ICB had a lower CD8 PET signal in the spleen and a higher CD4 PET signal in the spleen compared to non-responders. Intratumoral spatial heterogeneity of the CD8 and CD4-specific PET signals was lower in responders compared to non-responders. Finally, PET imaging, autoradiography, and immunofluorescence signals were correlated when comparing in vivo imaging to ex vivo validations. Conclusions CD4- and CD8-specific immuno-PET imaging can be used to characterize the in vivo distribution of CD4 + and CD8 + T cells in response to immune checkpoint blockade. Imaging metrics that describe the overall levels and distribution of CD8 + T cells and CD4 + T cells can provide insight into immunological alterations, predict biomarkers of response to immunotherapy, and guide clinical decision-making in those tumors where the kinetics of the response differ.

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“…IF staining was performed as described [21]. Briefly, paraffin-embedded tumors were sectioned as 5 μm slides and dewaxed with xylene.…”

Section: Immunofluorescence (If) Stainingmentioning

confidence: 99%

“…Finally, slides were mounted with DAPI mounting media (SouthernBiotech, 0100 − 20). High-resolution 20x images were acquired (EVOS M7000 Imaging System, Thermo Fisher Scientific, Waltham, MA) and CD4 + or CD8 + cells were quantified as previously reported (MATLAB) [21].…”

Section: Immunofluorescence (If) Stainingmentioning

confidence: 99%

Evaluating the immunologically “cold” tumor microenvironment after treatment with immune checkpoint inhibitors utilizing PET imaging of CD4 + and CD8 + T cells in breast cancer mouse models

Lu,

Houson,

Gallegos

et al. 2024

Breast Cancer Res

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“…The most straightforward use of the FUCCI system is to assess viability and global proliferation patterns at the tissue level [6,25]. For example, monitoring the ratio of cells that transition to S state in one culture sample that was pharmacologically manipulated, or implanted and then extracted from in situ growth [26]. The FUCCI system can then provide a powerful method to evaluate cell cycle related mechanisms, with the most pronounced one being studies of cell cycle targeted drugs for cancer growth suppression and metastatic inhibition [27][28][29].…”

Section: Tissue-level Monitoring For Cell Cycle Status During Collect...mentioning

confidence: 99%

ConfluentFUCCI for fully-automated analysis of cell-cycle progression in a highly dense collective of migrating cells

Goldstien,

Lavi,

Atia

2024

PLoS ONE

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Understanding mechanisms underlying various physiological and pathological processes often requires accurate and fully automated analysis of dense cell populations that collectively migrate. In such multicellular systems, there is a rising interest in the relations between biophysical and cell cycle progression aspects. A seminal tool that led to a leap in real-time study of cell cycle is the fluorescent ubiquitination-based cell cycle indicator (FUCCI). Here, we introduce ConfluentFUCCI, an open-source graphical user interface-based framework that is designed, unlike previous tools, for fully automated analysis of cell cycle progression, cellular dynamics, and cellular morphology, in highly dense migrating cell collectives. We integrated into ConfluentFUCCI’s pipeline state-of-the-art tools such as Cellpose, TrackMate, and Napari, some of which incorporate deep learning, and we wrap the entire tool into an isolated computational environment termed container. This provides an easy installation and workflow that is independent of any specific operation system. ConfluentFUCCI offers accurate nuclear segmentation and tracking using FUCCI tags, enabling comprehensive investigation of cell cycle progression at both the tissue and single-cell levels. We compare ConfluentFUCCI to the most recent relevant tool, showcasing its accuracy and efficiency in handling large datasets. Furthermore, we demonstrate the ability of ConfluentFUCCI to monitor cell cycle transitions, dynamics, and morphology within densely packed epithelial cell populations, enabling insights into mechanotransductive regulation of cell cycle progression. The presented tool provides a robust approach for investigating cell cycle-related phenomena in complex biological systems, offering potential applications in cancer research and other fields.

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“…The most straightforward use of the FUCCI system is to asses viability and global proliferation patterns at the tissue level [6,24]. For example, monitoring the ratio of cells that transition to S state in one culture sample that was pharmacologically manipulated, or implanted and then extracted from in situ growth [25]. The FUCCI system can then provide a powerful method to evaluate cell cycle related mechanisms, with the most pronounced one being studies of cell cycle targeted drugs for cancer growth suppression and metastatic inhibition [26][27][28].…”

Section: Tissue-level Monitoring For Cell Cycle Status During Collect...mentioning

confidence: 99%

ConfluentFUCCI for fully-automated analysis of cell-cycle progression in a highly dense collective of migrating cells

Goldstien,

Lavi,

Atia

2023

Preprint

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Understanding mechanisms underlying various physiological and pathological processes requires accurate and fully automated analysis of dense cell populations that collectively migrate, and specifically, relations between biophysical features and cell cycle progression aspects. A seminal tool that led to a leap in real-time study of cell cycle is the fluorescent ubiquitination-based cell cycle indicator (FUCCI). Here, we introduce ConfluentFUCCI, an open-source graphical user interface-based framework designed for fully automated analysis of cell cycle progression, cellular dynamics, and cellular morphology, in highly dense migrating cell collectives. Leveraging state-of-the-art tools, some incorporate deep learning, ConfluentFUCCI offers accurate nuclear segmentation and tracking using FUCCI tags, enabling comprehensive investigation of cell cycle progression at both the tissue and single-cell levels. We compare ConfluentFUCCI to the most recent relevant tool, showcasing its accuracy and efficiency in handling large datasets. Furthermore, we demonstrate the ability of ConfluentFUCCI to monitor cell cycle transitions, dynamics, and morphology within densely packed epithelial cell populations, enabling insights into mechanotransductive regulation of cell cycle progression. The presented tool provides a robust approach for investigating cell cycle-related phenomena in complex biological systems, offering potential applications in cancer research and other fields.

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Evaluating the Accuracy of FUCCI Cell Cycle In Vivo Fluorescent Imaging to Assess Tumor Proliferation in Preclinical Oncology Models

Cited by 3 publications

References 45 publications

Evaluating the immunologically “cold” tumor microenvironment after treatment with immune checkpoint inhibitors utilizing PET imaging of CD4 + and CD8 + T cells in breast cancer mouse models

Evaluating the immunologically “cold” tumor microenvironment after treatment with immune checkpoint inhibitors utilizing PET imaging of CD4 + and CD8 + T cells in breast cancer mouse models

ConfluentFUCCI for fully-automated analysis of cell-cycle progression in a highly dense collective of migrating cells

ConfluentFUCCI for fully-automated analysis of cell-cycle progression in a highly dense collective of migrating cells

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