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1.
JCI Insight ; 6(3)2021 02 08.
Article in English | MEDLINE | ID: mdl-33351787

ABSTRACT

Asymmetric cell division (ACD) enables the maintenance of a stem cell population while simultaneously generating differentiated progeny. Cancer stem cells (CSCs) undergo multiple modes of cell division during tumor expansion and in response to therapy, yet the functional consequences of these division modes remain to be determined. Using a fluorescent reporter for cell surface receptor distribution during mitosis, we found that ACD generated a daughter cell with enhanced therapeutic resistance and increased coenrichment of EGFR and neurotrophin receptor (p75NTR) from a glioblastoma CSC. Stimulation of both receptors antagonized differentiation induction and promoted self-renewal capacity. p75NTR knockdown enhanced the therapeutic efficacy of EGFR inhibition, indicating that coinheritance of p75NTR and EGFR promotes resistance to EGFR inhibition through a redundant mechanism. These data demonstrate that ACD produces progeny with coenriched growth factor receptors, which contributes to the generation of a more therapeutically resistant CSC population.


Subject(s)
Asymmetric Cell Division , Brain Neoplasms/drug therapy , Brain Neoplasms/pathology , Drug Resistance, Neoplasm , Glioblastoma/drug therapy , Glioblastoma/pathology , Neoplastic Stem Cells/drug effects , Neoplastic Stem Cells/pathology , AC133 Antigen/metabolism , Brain Neoplasms/metabolism , Cell Differentiation , Cell Line, Tumor , Cell Self Renewal , ErbB Receptors/antagonists & inhibitors , ErbB Receptors/metabolism , Gene Knockdown Techniques , Glioblastoma/metabolism , Humans , Neoplastic Stem Cells/metabolism , Nerve Tissue Proteins/antagonists & inhibitors , Nerve Tissue Proteins/genetics , Nerve Tissue Proteins/metabolism , Receptors, Nerve Growth Factor/antagonists & inhibitors , Receptors, Nerve Growth Factor/genetics , Receptors, Nerve Growth Factor/metabolism
2.
Cytometry A ; 95(3): 290-301, 2019 03.
Article in English | MEDLINE | ID: mdl-30729665

ABSTRACT

Cancer stem cells (CSCs) are a heterogeneous and dynamic self-renewing population that stands at the top of tumor cellular hierarchy and contribute to tumor recurrence and therapeutic resistance. As methods of CSC isolation and functional interrogation advance, there is a need for a reliable and accessible quantitative approach to assess heterogeneity and state transition dynamics in CSCs. We developed a high-throughput automated single cell imaging analysis (HASCIA) approach for the quantitative assessment of protein expression with single-cell resolution and applied the method to investigate spatiotemporal factors that influence CSC state transition using glioblastoma (GBM) CSCs (GSCs) as a model system. We were able to validate the quantitative nature of this approach through comparison of the protein expression levels determined by HASCIA to those determined by immunoblotting. A virtue of HASCIA was exemplified by detection of a subpopulation of SOX2-low cells, which expanded in fraction size during state transition. HASCIA also revealed that GSCs were committed to loose stem cell state at an earlier time point than the average SOX2 level decreased. Functional assessment of stem cell frequency in combination with the quantification of SOX2 expression by HASCIA defined a stable cutoff of SOX2 expression level for stem cell state. We also developed an approach to assess local cell density and found that denser monolayer areas possess higher average levels of SOX2, higher cell diversity, and a presence of a sub-population of slowly proliferating SOX2-low GSCs. HASCIA is an open source software that facilitates understanding the dynamics of heterogeneous cell population such as that of GSCs and their progeny. It is a powerful and easy-to-use image analysis and statistical analysis tool available at https://hascia.lerner.ccf.org. © 2019 International Society for Advancement of Cytometry.


Subject(s)
Image Processing, Computer-Assisted/methods , Neoplastic Stem Cells/cytology , Neoplastic Stem Cells/metabolism , SOXB1 Transcription Factors/metabolism , Single-Cell Analysis/methods , Animals , Brain Neoplasms/genetics , Brain Neoplasms/metabolism , Cell Count , Cell Line, Tumor , Cell Proliferation/genetics , Cells, Cultured , ErbB Receptors/genetics , ErbB Receptors/metabolism , Female , Gene Expression Regulation, Neoplastic , Glioblastoma/genetics , Glioblastoma/metabolism , Humans , Mice , Mice, Inbred NOD , Neoplastic Stem Cells/ultrastructure , SOXB1 Transcription Factors/analysis , SOXB1 Transcription Factors/genetics , STAT3 Transcription Factor/genetics , STAT3 Transcription Factor/metabolism , Software
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