Comparative analyses of Purkinje cell gene expression profiles reveal shared molecular abnormalities in models of different polyglutamine diseases

2012 ◽  
Vol 1481 ◽  
pp. 37-48 ◽  
Author(s):  
Bernd Friedrich ◽  
Philipp Euler ◽  
Ruhtraut Ziegler ◽  
Alexandre Kuhn ◽  
Bernhard G. Landwehrmeyer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Purkinje Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Polyglutamine Diseases ◽  
Comparative Analyses ◽  
Molecular Abnormalities ◽  
Cell Gene Expression ◽  
Cell Gene

The t(14;18) defines a unique subset of diffuse large B-cell lymphoma with a germinal center B-cell gene expression profile

Blood ◽  
2002 ◽  
Vol 99 (7) ◽  
pp. 2285-2290 ◽  
Author(s):  
James Z. Huang ◽  
Warren G. Sanger ◽  
Timothy C. Greiner ◽  
Louis M. Staudt ◽  
Dennis D. Weisenburger ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profile ◽  
Expression Profile ◽  
Germinal Center ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Germinal Center B Cell ◽  
Cell Gene Expression ◽  
Cell Gene

Recently we have identified subgroups of de novo primary diffuse large B-cell lymphoma (DLBCL) based on complementary DNA microarray-generated gene expression profiles. To correlate the gene expression profiles with cytogenetic abnormalities in these DLBCLs, we examined the occurrence of the t(14;18)(q32;q21) in the 2 distinctive subgroups of DLBCL: one with the germinal center B-cell gene expression signature and the other with the activated B cell–like gene expression signature. The t(14;18) was detected in 7 of 35 cases (20%). All 7 t(14;18)-positive cases had a germinal center B-cell gene expression profile, representing 35% of the cases in this subgroup, and 6 of these 7 cases had very similar gene expression profiles. The expression of bcl-2 and bcl-6 proteins was not significantly different between the t(14;18)-positive and -negative cases, whereas CD10 was detected only in the group with the germinal center B-cell expression profile, and CD10 was most frequently expressed in the t(14;18)-positive cases. This study supports the validity of subdividing DLBCL into 2 major subgroups by gene expression profiling, with the t(14;18) being an important event in the pathogenesis of a subset of DLBCL arising from germinal center B cells. CD10 protein expression is useful in identifying cases of DLBCL with a germinal center B-cell gene expression profile and is often expressed in cases with the t(14;18).

scholarly journals The single-cell transcriptional landscape of lung carcinoid tumors

2021 ◽  
Author(s):  
Philip Bischoff ◽  
Alexandra Trinks ◽  
Jennifer Wiederspahn ◽  
Benedikt Obermayer ◽  
Jan Patrick Pett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Carcinoid Tumor ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Carcinoid Tumors ◽  
Cellular Composition ◽  
Cell Gene Expression ◽  
Cell Gene ◽  
Lung Carcinoid

AbstractLung carcinoid tumors, also referred to as pulmonary neuroendocrine tumors or lung carcinoids, are rare neoplasms of the lung with a more favorable prognosis than other subtypes of lung cancer. Still, some patients suffer from relapsed disease and metastatic spread while no consensus treatment exists for metastasized carcinoids. Several recent single-cell studies have provided detailed insights into the cellular heterogeneity of more common lung cancers, such as adeno- and squamous cell carcinoma. However, the characteristics of lung carcinoids on the single-cell level are yet completely unknown.To study the cellular composition and single-cell gene expression profiles in lung carcinoids, we applied single-cell RNA sequencing to three lung carcinoid tumor samples and normal lung tissue. The single-cell transcriptomes of carcinoid tumor cells reflected intertumoral heterogeneity associated with clinicopathological features, such as tumor necrosis and proliferation index. The immune microenvironment was specifically enriched in noninflammatory monocyte-derived myeloid cells. Tumor-associated endothelial cells were characterized by distinct gene expression profiles. A spectrum of vascular smooth muscle cells and pericytes predominated the stromal microenvironment. We found a small proportion of myofibroblasts exhibiting features reminiscent of cancer-associated fibroblasts. Stromal and immune cells exhibited potential paracrine interactions which may shape the microenvironment via NOTCH, VEGF, TGFβ and JAK/STAT signaling. Moreover, single-cell gene signatures of pericytes and myofibroblasts demonstrated prognostic value in bulk gene expression data.Here, we provide first comprehensive insights into the cellular composition and single-cell gene expression profiles in lung carcinoids, demonstrating the non-inflammatory and vessel-rich nature of their tumor microenvironment, and outlining relevant intercellular interactions which could serve as future therapeutic targets.

Correlation of Murine Embryonic Stem Cell Gene Expression Profiles with Functional Measures of Pluripotency

Stem Cells ◽  
2005 ◽  
Vol 23 (5) ◽  
pp. 663-680 ◽  
Author(s):  
Lars Palmqvist ◽  
Clive H. Glover ◽  
Lien Hsu ◽  
Min Lu ◽  
Bolette Bossen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Embryonic Stem Cell ◽  
Expression Profiles ◽  
Embryonic Stem ◽  
Gene Expression Profiles ◽  
Murine Embryonic Stem Cell ◽  
Cell Gene Expression ◽  
Cell Gene ◽  
Stem Cell Gene

scholarly journals Single-nucleus RNA-seq identifies Huntington disease astrocyte states

2019 ◽  
Author(s):  
Osama Al-Dalahmah ◽  
Alexander A Sosunov ◽  
A Shaik ◽  
Kenneth Ofori ◽  
Yang Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Huntington Disease ◽  
Expression Profiles ◽  
Lipid Synthesis ◽  
Gene Expression Profiles ◽  
Cag Repeats ◽  
Cell Gene Expression ◽  
Single Nucleus ◽  
Cell Gene

AbstractHuntington Disease (HD) is an inherited movement disorder caused by expanded CAG repeats in the Huntingtin gene. We have used single nucleus RNASeq (snRNASeq) to uncover cellular phenotypes that change in the disease, investigating single cell gene expression in cingulate cortex of patients with HD and comparing the gene expression to that of patients with no neurological disease. In this study, we focused on astrocytes, although we found significant gene expression differences in neurons, oligodendrocytes, and microglia as well. In particular, the gene expression profiles of astrocytes in HD showed multiple signatures, varying in phenotype from cells that had markedly upregulated metallothionein and heat shock genes, but had not completely lost the expression of genes associated with normal protoplasmic astrocytes, to astrocytes that had substantially upregulated GFAP and had lost expression of many normal protoplasmic astrocyte genes as well as metallothionein genes. When compared to astrocytes in control samples, astrocyte signatures in HD also showed downregulated expression of a number of genes, including several associated with protoplasmic astrocyte function and lipid synthesis. Thus, HD astrocytes appeared in variable transcriptional phenotypes, and could be divided into several different “states”, defined by patterns of gene expression. Ultimately, this study begins to fill the knowledge gap of single cell gene expression in HD and provide a more detailed understanding of the variation in changes in gene expression during astrocyte “reactions” to the disease.

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