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 ◽  
...  

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.

2019 ◽  
Author(s):  
Osama Al-Dalahmah ◽  
Alexander A Sosunov ◽  
A Shaik ◽  
Kenneth Ofori ◽  
Yang Liu ◽  
...  

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.


2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Idan Efroni ◽  
Pui-Leng Ip ◽  
Tal Nawy ◽  
Alison Mello ◽  
Kenneth D Birnbaum

2014 ◽  
Vol 2 (6) ◽  
pp. 881-895 ◽  
Author(s):  
Shelley R. Hough ◽  
Matthew Thornton ◽  
Elizabeth Mason ◽  
Jessica C. Mar ◽  
Christine A. Wells ◽  
...  

2016 ◽  
Author(s):  
Laleh Haghverdi ◽  
Maren Büttner ◽  
F. Alexander Wolf ◽  
Florian Buettner ◽  
Fabian J. Theis

Single-cell gene expression profiles of differentiating cells encode their intrinsic latent temporal order. We describe an efficient way to robustly estimate this order according to a diffusion pseudotime, which measures transitions on all length scales between cells using diffusion-like random walks. This allows us to identify cells that undergo branching decisions or are in metastable states, and thereby genes differentially regulated at these states.


2020 ◽  
Author(s):  
Michelangelo Cordenonsi ◽  
Silvio Bicciato ◽  
Stefano Piccolo

Abstract We describe a multistep computational procedure to identify candidate master Transcriptional Regulators (TRs) of glioblastoma (GBM) from glioblastoma single cell gene expression profiles and tissue-specific transcription factors.


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