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Article ; Online: Modeling tuberous sclerosis with organoids.

Ihrie, Rebecca A / Henske, Elizabeth P

2022 Volume 375, Issue 6579, Page(s) 382–383

Abstract: Figure: see text]. ...

Abstract	[Figure: see text].
MeSH term(s)	Humans ; Organoids ; Tuberous Sclerosis/genetics
Language	English
Publishing date	2022-01-27
Publishing country	United States
Document type	Journal Article ; Comment
ZDB-ID	128410-1
ISSN	1095-9203 ; 0036-8075
ISSN (online)	1095-9203
ISSN	0036-8075
DOI	10.1126/science.abn6158
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Zs.MG 77: Show issues

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Article ; Online: Learning cell identity in immunology, neuroscience, and cancer

Medina, Stephanie / Ihrie, Rebecca A. / Irish, Jonathan M.

Semin Immunopathol. 2023 Jan., v. 45, no. 1, p. 3-16

2023 , Page(s) 3–16

Abstract: Suspension and imaging cytometry techniques that simultaneously measure hundreds of cellular features are powering a new era of cell biology and transforming our understanding of human tissues and tumors. However, a central challenge remains in learning ... ...

Abstract	Suspension and imaging cytometry techniques that simultaneously measure hundreds of cellular features are powering a new era of cell biology and transforming our understanding of human tissues and tumors. However, a central challenge remains in learning the identities of unexpected or novel cell types. Cell identification rubrics that could assist trainees, whether human or machine, are not always rigorously defined, vary greatly by field, and differentially rely on cell intrinsic measurements, cell extrinsic tissue measurements, or external contextual information such as clinical outcomes. This challenge is especially acute in the context of tumors, where cells aberrantly express developmental programs that are normally time, location, or cell-type restricted. Well-established fields have contrasting practices for cell identity that have emerged from convention and convenience as much as design. For example, early immunology focused on identifying minimal sets of protein features that mark individual, functionally distinct cells. In neuroscience, features including morphology, development, and anatomical location were typical starting points for defining cell types. Both immunology and neuroscience now aim to link standardized measurements of protein or RNA to informative cell functions such as electrophysiology, connectivity, lineage potential, phospho-protein signaling, cell suppression, and tumor cell killing ability. The expansion of automated, machine-driven methods for learning cell identity has further created an urgent need for a harmonized framework for distinguishing cell identity across fields and technology platforms. Here, we compare practices in the fields of immunology and neuroscience, highlight concepts from each that might work well in the other, and propose ways to implement these ideas to study neural and immune cell interactions in brain tumors and associated model systems.
Keywords	RNA ; automation ; brain ; electrophysiology ; humans ; immunology ; neoplasm cells ; neurophysiology
Language	English
Dates of publication	2023-01
Size	p. 3-16
Publishing place	Springer Berlin Heidelberg
Document type	Article ; Online
Note	Review
ZDB-ID	2316828-6
ISSN	1863-2300 ; 1863-2297
ISSN (online)	1863-2300
ISSN	1863-2297
DOI	10.1007/s00281-022-00976-y
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Learning cell identity in immunology, neuroscience, and cancer.

Medina, Stephanie / Ihrie, Rebecca A / Irish, Jonathan M

Seminars in immunopathology

2022 Volume 45, Issue 1, Page(s) 3–16

Abstract	Suspension and imaging cytometry techniques that simultaneously measure hundreds of cellular features are powering a new era of cell biology and transforming our understanding of human tissues and tumors. However, a central challenge remains in learning the identities of unexpected or novel cell types. Cell identification rubrics that could assist trainees, whether human or machine, are not always rigorously defined, vary greatly by field, and differentially rely on cell intrinsic measurements, cell extrinsic tissue measurements, or external contextual information such as clinical outcomes. This challenge is especially acute in the context of tumors, where cells aberrantly express developmental programs that are normally time, location, or cell-type restricted. Well-established fields have contrasting practices for cell identity that have emerged from convention and convenience as much as design. For example, early immunology focused on identifying minimal sets of protein features that mark individual, functionally distinct cells. In neuroscience, features including morphology, development, and anatomical location were typical starting points for defining cell types. Both immunology and neuroscience now aim to link standardized measurements of protein or RNA to informative cell functions such as electrophysiology, connectivity, lineage potential, phospho-protein signaling, cell suppression, and tumor cell killing ability. The expansion of automated, machine-driven methods for learning cell identity has further created an urgent need for a harmonized framework for distinguishing cell identity across fields and technology platforms. Here, we compare practices in the fields of immunology and neuroscience, highlight concepts from each that might work well in the other, and propose ways to implement these ideas to study neural and immune cell interactions in brain tumors and associated model systems.
MeSH term(s)	Humans ; Neoplasms/etiology ; Image Cytometry ; Image Interpretation, Computer-Assisted
Language	English
Publishing date	2022-12-19
Publishing country	Germany
Document type	Journal Article ; Review ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2316828-6
ISSN	1863-2300 ; 1863-2297
ISSN (online)	1863-2300
ISSN	1863-2297
DOI	10.1007/s00281-022-00976-y
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Article ; Online: Histological Studies of the Ventricular-Subventricular Zone as Neural Stem Cell and Glioma Stem Cell Niche.

Brockman, Asa A / Mobley, Bret C / Ihrie, Rebecca A

The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society

2021 Volume 69, Issue 12, Page(s) 819–834

Abstract: The neural stem cell niche of the ventricular-subventricular zone supports the persistence of stem and progenitor cells in the mature brain. This niche has many notable cytoarchitectural features that affect the activity of stem cells and may also ... ...

Abstract	The neural stem cell niche of the ventricular-subventricular zone supports the persistence of stem and progenitor cells in the mature brain. This niche has many notable cytoarchitectural features that affect the activity of stem cells and may also support the survival and growth of invading tumor cells. Histochemical studies of the niche have revealed many proteins that, in combination, can help to reveal stem-like cells in the normal or cancer context, although many caveats persist in the quest to consistently identify these cells in the human brain. Here, we explore the complex relationship between the persistent proliferative capacity of the neural stem cell niche and the malignant proliferation of brain tumors, with a special focus on histochemical identification of stem cells and stem-like tumor cells and an eye toward the potential application of high-dimensional imaging approaches to the field.
MeSH term(s)	Animals ; Brain ; Brain Neoplasms/diagnostic imaging ; Brain Neoplasms/metabolism ; Cell Differentiation ; Cell Proliferation ; Doublecortin Domain Proteins/metabolism ; Glioma/diagnostic imaging ; Glioma/metabolism ; Humans ; Lateral Ventricles/diagnostic imaging ; Lateral Ventricles/metabolism ; Neoplastic Stem Cells ; Nestin/metabolism ; Neural Stem Cells/metabolism ; Stem Cell Niche/physiology
Chemical Substances	Doublecortin Domain Proteins ; Nestin
Language	English
Publishing date	2021-07-26
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S. ; Review
ZDB-ID	218208-7
ISSN	1551-5044 ; 0022-1554
ISSN (online)	1551-5044
ISSN	0022-1554
DOI	10.1369/00221554211032003
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Article ; Online: Non-canonical functions of a mutant TSC2 protein in mitotic division.

Chalkley, Mary-Bronwen L / Mersfelder, Rachel B / Sundberg, Maria / Armstrong, Laura C / Sahin, Mustafa / Ihrie, Rebecca A / Ess, Kevin C

PloS one

2023 Volume 18, Issue 10, Page(s) e0292086

Abstract: Tuberous Sclerosis Complex (TSC) is a debilitating developmental disorder characterized by a variety of clinical manifestations. TSC is caused by mutations in the TSC1 or TSC2 genes, which encode the hamartin/tuberin proteins respectively. These proteins ...

Abstract	Tuberous Sclerosis Complex (TSC) is a debilitating developmental disorder characterized by a variety of clinical manifestations. TSC is caused by mutations in the TSC1 or TSC2 genes, which encode the hamartin/tuberin proteins respectively. These proteins function as a heterodimer that negatively regulates the mechanistic Target of Rapamycin Complex 1 (mTORC1). TSC research has focused on the effects of mTORC1, a critical signaling hub, on regulation of diverse cell processes including metabolism, cell growth, translation, and neurogenesis. However, non-canonical functions of TSC2 are not well studied, and the potential disease-relevant biological mechanisms of mutations affecting these functions are not well understood. We observed aberrant multipolar mitotic division, a novel phenotype, in TSC2 mutant iPSCs. The multipolar phenotype is not meaningfully affected by treatment with the inhibitor rapamycin. We further observed dominant negative activity of the mutant form of TSC2 in producing the multipolar division phenotype. These data expand the knowledge of TSC2 function and pathophysiology which will be highly relevant to future treatments for patients with TSC.
MeSH term(s)	Humans ; Mechanistic Target of Rapamycin Complex 1/genetics ; Mechanistic Target of Rapamycin Complex 1/metabolism ; Mutant Proteins ; Signal Transduction ; Tuberous Sclerosis Complex 2 Protein/genetics ; Tuberous Sclerosis Complex 2 Protein/metabolism ; Tumor Suppressor Proteins/genetics ; Tumor Suppressor Proteins/metabolism
Chemical Substances	Mechanistic Target of Rapamycin Complex 1 (EC 2.7.11.1) ; Mutant Proteins ; Tuberous Sclerosis Complex 2 Protein ; Tumor Suppressor Proteins ; TSC2 protein, human
Language	English
Publishing date	2023-10-04
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0292086
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Article: Heterogeneity of Neural Stem Cells in the Ventricular-Subventricular Zone.

Rushing, Gabrielle V / Bollig, Madelyn K / Ihrie, Rebecca A

Advances in experimental medicine and biology

2019 Volume 1169, Page(s) 1–30

Abstract: In this chapter, heterogeneity is explored in the context of the ventricular-subventricular zone, the largest stem cell niche in the mammalian brain. This niche generates up to 10,000 new neurons daily in adult mice and extends over a large spatial area ... ...

Abstract	In this chapter, heterogeneity is explored in the context of the ventricular-subventricular zone, the largest stem cell niche in the mammalian brain. This niche generates up to 10,000 new neurons daily in adult mice and extends over a large spatial area with dorso-ventral and medio-lateral subdivisions. The stem cells of the ventricular-subventricular zone can be subdivided by their anatomical position and transcriptional profile, and the stem cell lineage can also be further subdivided into stages of pre- and post-natal quiescence and activation. Beyond the stem cells proper, additional differences exist in their interactions with other cellular constituents of the niche, including neurons, vasculature, and cerebrospinal fluid. These variations in stem cell potential and local interactions are discussed, as well as unanswered questions within this system.
MeSH term(s)	Animals ; Brain/cytology ; Cell Lineage ; Lateral Ventricles/cytology ; Mice ; Neural Stem Cells/cytology ; Neurons/cytology ; Stem Cell Niche/physiology
Language	English
Publishing date	2019-09-05
Publishing country	United States
Document type	Journal Article
ISSN	2214-8019 ; 0065-2598
ISSN (online)	2214-8019
ISSN	0065-2598
DOI	10.1007/978-3-030-24108-7_1
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Article: IL-8 Instructs Macrophage Identity in Lateral Ventricle Contacting Glioblastoma.

Medina, Stephanie / Brockman, Asa A / Cross, Claire E / Hayes, Madeline J / Mobley, Bret C / Mistry, Akshitkumar M / Chotai, Silky / Weaver, Kyle D / Thompson, Reid C / Chambless, Lola B / Ihrie, Rebecca A / Irish, Jonathan M

bioRxiv : the preprint server for biology

2024

Abstract: Adult IDH-wildtype glioblastoma (GBM) is a highly aggressive brain tumor with no established immunotherapy or targeted therapy. Recently, ... ...

Abstract	Adult IDH-wildtype glioblastoma (GBM) is a highly aggressive brain tumor with no established immunotherapy or targeted therapy. Recently, CD32
Language	English
Publishing date	2024-03-30
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.03.29.587030
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Article: Velociraptor: Cross-Platform Quantitative Search Using Hallmark Cell Features.

Cross, Claire E / Mayeda, Cass / Medina, Stephanie / Hayes, Madeline J / Kaviany, Saara / Connelly, James A / Rathmell, Jeffrey C / Weaver, Kyle D / Thompson, Reid C / Chambless, Lola B / Ihrie, Rebecca A / Irish, Jonathan M

bioRxiv : the preprint server for biology

2024

Abstract: A key challenge for single cell discovery analysis is to identify new cell types, describe them quantitatively, and seek these novel cells in new studies often using a different platform. Over the last decade, tools were developed to address ... ...

Abstract	A key challenge for single cell discovery analysis is to identify new cell types, describe them quantitatively, and seek these novel cells in new studies often using a different platform. Over the last decade, tools were developed to address identification and quantitative description of cells in human tissues and tumors. However, automated validation of populations at the single cell level has struggled due to the cytometry field's reliance on hierarchical, ordered use of features and on platform-specific rules for data processing and analysis. Here we present Velociraptor, a workflow that implements Marker Enrichment Modeling in three cross-platform modules: 1) identification of cells specific to disease states, 2) description of hallmark features for each cell and population, and 3) searching for cells matching one or more hallmark feature sets in a new dataset. A key advance is that Velociraptor registers cells between datasets, including between flow cytometry and quantitative imaging using different, overlapping feature sets. Four datasets were used to challenge Velociraptor and reveal new biological insights. Working at the individual sample level, Velociraptor tracked the abundance of clinically significant glioblastoma brain tumor cell subsets and characterized the cells that predominate in recurrent tumors as a close match for rare, negative prognostic cells originally observed in matched pre-treatment tumors. In patients with inborn errors of immunity, Velociraptor identified genotype-specific cells associated with
Language	English
Publishing date	2024-05-04
Publishing country	United States
Document type	Preprint
DOI	10.1101/2024.05.01.591375
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Article: Neural stem cell heterogeneity through time and space in the ventricular-subventricular zone.

Rushing, Gabrielle / Ihrie, Rebecca A

Frontiers in biology

2016 Volume 11, Issue 4, Page(s) 261–284

Abstract: Background: The origin and classification of neural stem cells (NSCs) has been a subject of intense investigation for the past two decades. Efforts to categorize NSCs based on their location, function and expression have established that these cells are ...

Abstract	Background: The origin and classification of neural stem cells (NSCs) has been a subject of intense investigation for the past two decades. Efforts to categorize NSCs based on their location, function and expression have established that these cells are a heterogeneous pool in both the embryonic and adult brain. The discovery and additional characterization of adult NSCs has introduced the possibility of using these cells as a source for neuronal and glial replacement following injury or disease. To understand how one could manipulate NSC developmental programs for therapeutic use, additional work is needed to elucidate how NSCs are programmed and how signals during development are interpreted to determine cell fate. Objective: This review describes the identification, classification and characterization of NSCs within the large neurogenic niche of the ventricular-subventricular zone (V-SVZ). Methods: A literature search was conducted using Pubmed including the keywords "ventricular-subventricular zone," "neural stem cell," "heterogeneity," "identity" and/or "single cell" to find relevant manuscripts to include within the review. A special focus was placed on more recent findings using single-cell level analyses on neural stem cells within their niche(s). Results: This review discusses over 20 research articles detailing findings on V-SVZ NSC heterogeneity, over 25 articles describing fate determinants of NSCs, and focuses on 8 recent publications using distinct single-cell analyses of neural stem cells including flow cytometry and RNA-seq. Additionally, over 60 manuscripts highlighting the markers expressed on cells within the NSC lineage are included in a chart divided by cell type. Conclusions: Investigation of NSC heterogeneity and fate decisions is ongoing. Thus far, much research has been conducted in mice however, findings in human and other mammalian species are also discussed here. Implications of NSC heterogeneity established in the embryo for the properties of NSCs in the adult brain are explored, including how these cells may be redirected after injury or genetic manipulation.
Language	English
Publishing date	2016-07-08
Publishing country	China
Document type	Journal Article
ZDB-ID	2658772-5
ISSN	1674-7992 ; 1674-7984
ISSN (online)	1674-7992
ISSN	1674-7984
DOI	10.1007/s11515-016-1407-1
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Article ; Online: Head of the Class: OLIG2 and Glioblastoma Phenotype.

Leelatian, Nalin / Ihrie, Rebecca A

Cancer cell

2016 Volume 29, Issue 5, Page(s) 613–615

Abstract: Genomic mapping has driven the classification of glioblastoma into distinct molecular subclasses, but mechanisms that regulate tumor subclass phenotypes are only now emerging. In this issue of Cancer Cell, Lu et al. describe a phenotypic switch from ... ...

Abstract	Genomic mapping has driven the classification of glioblastoma into distinct molecular subclasses, but mechanisms that regulate tumor subclass phenotypes are only now emerging. In this issue of Cancer Cell, Lu et al. describe a phenotypic switch from PDGFRA-enriched "proneural" to EGFR-enriched "classical" features in glioblastoma upon ablation of Olig2.
MeSH term(s)	Brain Neoplasms/genetics ; Glioblastoma/genetics ; Humans ; Phenotype ; Transcription Factors/genetics
Chemical Substances	Transcription Factors
Language	English
Publishing date	2016--09
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Comment
ZDB-ID	2078448-X
ISSN	1878-3686 ; 1535-6108
ISSN (online)	1878-3686
ISSN	1535-6108
DOI	10.1016/j.ccell.2016.04.007
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