scholarly journals TMOD-11. CHARACTERISATION OF THE POST-SURGICAL INVASIVE TUMOUR NICHE USING ASTROCYTE-GLIOBLASTOMA ORGANOIDS AND DECELLULARISED HUMAN BRAIN

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi264-vi265
Author(s):  
Mohammed Diksin ◽  
Jonathan Rowlinson ◽  
Alexander Kondrashov ◽  
Chris Denning ◽  
Jaime Hughes ◽  
...  
Keyword(s):  
Human Brain ◽  
Rna Sequencing ◽  
Cross Talk ◽  
Chromosome 1 ◽  
Brain Extract ◽  
Malignant Cells ◽  
Sequencing Data ◽  
Glioma Invasion ◽  
Naive Patient ◽  
Invasive Margin

Abstract Glioblastoma therapeutic challenges are in considerable part due to myriad survival mechanisms which allow malignant cells to repurpose signalling pathways within discreet microenvironments. These Darwinian adaptations facilitate invasion into brain parenchyma and perivascular space. We hypothesised that pre-clinical modelling of glioma invasion by recapitulating early events occurring immediately after surgery at the glioblastoma invasive margin, could reveal the cross-talk between malignant cells and surrounding healthy astrocytes. We first generated transgenic H1-derived neural stem cells using CRISPR/Cas9-mediated knock-in of the YFP reporter gene under the control of the GFAP promoter at the AAVS1 safe harbour locus. Reproducible ultrahigh-throughput AggreWells™ (7200 mini-wells per plate) were used to create astrocyte-glioblastoma organoids, which we term ‘Gliomasphere Matrices’. YFP-labelled astrocytes were co-cultured with 10 treatment-naïve patient-derived cell lines isolated from the 5-aminolevulinic (5ALA)-determined glioblastoma invasive margin. Co-cultures were seeded upon a sequentially constructed, time-of-flight secondary ion mass spectrometry (ToF-SIMS)-characterised decellularised human brain extract. YFP-astrocytes were purified from each of the 10 Gliomasphere Matrices using fluorescence-activated cell sorting (FACS) after 6- and 10-days co-culture. RNA-sequencing of the putatively reprogrammed YFP-astrocytes showed the characteristic expression of canonical key regulators of multiple malignant diseases including high-grade glioma such as SND1 and EFNB2 in addition to the identification of a single novel marker located at chromosome 1 (C1orf61), highly expressed in malignant glioma when compared to somatic cancers according to TCGA RNA-sequencing data. Differentiated YFP-astrocytes also overexpressed IFITM2 and IFITM10, known to be involved in priming resistance against pathogenic microorganisms. This ultimately suggests a fluctuating state between malignant transformation imposed by the highly infiltrative glioma cells and the counter-action of the normal astrocytes to these deleterious invasive cells. This multi-faceted model offers a unique opportunity to recapitulate early molecular cross-talk which facilitates glioblastoma recurrence and may be utilised for high-throughput drug screening.

scholarly journals Characterisation of the invasive tumour niche using astrocyte-glioblastoma organoids and decellularised human brain

2019 ◽  
Vol 21 (Supplement_4) ◽  
pp. iv7-iv7
Author(s):  
Mohammed Diksin ◽  
Jonathan Rowlinson ◽  
Alexandar Kondrashov ◽  
Chris Denning ◽  
Jamie Hughes ◽  
...  
Keyword(s):  
Human Brain ◽  
Cross Talk ◽  
Secondary Ion Mass Spectrometry ◽  
Brain Parenchyma ◽  
Brain Extract ◽  
Malignant Cells ◽  
3D Scaffold ◽  
Glioma Invasion ◽  
Naive Patient ◽  
Invasive Margin

Abstract Glioblastoma therapeutic challenges are in considerable part due to myriad survival adaptations and mechanisms, which allow malignant cells to repurpose signalling pathways within discreet microenvironments. These Darwinian adaptations facilitate invasion into brain parenchyma and perivascular space or promote evasion from repressive factors that represent anti-cancer defence mechanisms. We hypothesised that pre-clinical modelling of glioma invasion by recapitulating early events occurring immediately after surgery at the glioblastoma invasive margin, could reveal the cross-talk between malignant cells and the surrounding healthy astrocytes, which facilitates tumour recurrence. We first generated transgenic H1-derived neural stem cells using CRISPR/Cas9-mediated knock-in of the YFP reporter gene under the control of the GFAP promoter. Reproducible ultrahigh-throughput AggreWells™ (19,200 micro-wells per 24-well plate) were used to create astrocyte-glioblastoma organoids, which we term ‘Gliomasphere Matrices’. YFP-labelled astrocytes were co-cultured with 10 treatment-naïve patient-derived cell lines isolated from the 5-aminolevulinic (5ALA)-determined glioblastoma invasive margin. Co-cultures were seeded upon on a sequentially constructed, time-of-flight secondary ion mass spectrometry (ToF-SIMS)-characterised 3D scaffold, composed of decellularised human brain extract with defined PEGDA hydrogel. YFP-astrocytes were purified from each of the 10 Gliomasphere Matrices using fluorescence-activated cell sorting (FACS) after 6- and 10-days co-culture. RNAseq profiling to address both putative astrocytic reprogramming by invasive glioblastoma cells and gene expression changes intrinsic to tumour cells will be discussed in relation to RNAseq data from patient-derived 5ALA FACS-purified glioblastoma invasive margin tissue. This novel multi-faceted model offers a unique opportunity to recapitulate early molecular cross-talk which facilitates glioblastoma recurrence and may be utilised for high-throughput drug screening.

scholarly journals The Crosstalk Between Malignant Cells and Tumor-Promoting Immune Cells Relevant to Immunotherapy in Pancreatic Ductal Adenocarcinoma

2022 ◽  
Vol 9 ◽  
Author(s):  
Xuefei Liu ◽  
Ziwei Luo ◽  
Xuechen Ren ◽  
Zhihang Chen ◽  
Xiaoqiong Bao ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Rna Sequencing ◽  
Immune Cells ◽  
Immune Checkpoint ◽  
Immune Cell ◽  
Immune Checkpoint Blockade ◽  
Ductal Adenocarcinoma ◽  
Malignant Cells ◽  
Sequencing Data ◽  
Immunosuppressive Microenvironment

Background: Pancreatic ductal adenocarcinoma (PDAC) is dominated by an immunosuppressive microenvironment, which makes immune checkpoint blockade (ICB) often non-responsive. Understanding the mechanisms by which PDAC forms an immunosuppressive microenvironment is important for the development of new effective immunotherapy strategies.Methods: This study comprehensively evaluated the cell-cell communications between malignant cells and immune cells by integrative analyses of single-cell RNA sequencing data and bulk RNA sequencing data of PDAC. A Malignant-Immune cell crosstalk (MIT) score was constructed to predict survival and therapy response in PDAC patients. Immunological characteristics, enriched pathways, and mutations were evaluated in high- and low MIT groups.Results: We found that PDAC had high level of immune cell infiltrations, mainly were tumor-promoting immune cells. Frequent communication between malignant cells and tumor-promoting immune cells were observed. 15 ligand-receptor pairs between malignant cells and tumor-promoting immune cells were identified. We selected genes highly expressed on malignant cells to construct a Malignant-Immune Crosstalk (MIT) score. MIT score was positively correlated with tumor-promoting immune infiltrations. PDAC patients with high MIT score usually had a worse response to immune checkpoint blockade (ICB) immunotherapy.Conclusion: The ligand-receptor pairs identified in this study may provide potential targets for the development of new immunotherapy strategy. MIT score was established to measure tumor-promoting immunocyte infiltration. It can serve as a prognostic indicator for long-term survival of PDAC, and a predictor to ICB immunotherapy response.

scholarly journals A map of tumor–host interactions in glioma at single-cell resolution

GigaScience ◽  
2020 ◽  
Vol 9 (10) ◽  
Author(s):  
Francesca Pia Caruso ◽  
Luciano Garofano ◽  
Fulvio D'Angelo ◽  
Kai Yu ◽  
Fuchou Tang ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cross Talk ◽  
Large Scale ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Sequencing Data ◽  
Host Interaction ◽  
Receptor Interactions ◽  
Single Cell Rna Sequencing

ABSTRACT Background Single-cell RNA sequencing is the reference technique for characterizing the heterogeneity of the tumor microenvironment. The composition of the various cell types making up the microenvironment can significantly affect the way in which the immune system activates cancer rejection mechanisms. Understanding the cross-talk signals between immune cells and cancer cells is of fundamental importance for the identification of immuno-oncology therapeutic targets. Results We present a novel method, single-cell Tumor–Host Interaction tool (scTHI), to identify significantly activated ligand–receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand–receptor interactions in glioma using 6 publicly available human glioma datasets encompassing 57,060 gene expression profiles from 71 patients. By leveraging this large-scale collection we show that unexpected cross-talk partners are highly conserved across different datasets in the majority of the tumor samples. This suggests that shared cross-talk mechanisms exist in glioma. Conclusions Our results provide a complete map of the active tumor–host interaction pairs in glioma that can be therapeutically exploited to reduce the immunosuppressive action of the microenvironment in brain tumor.

scholarly journals FR-Match: Robust matching of cell type clusters from single cell RNA sequencing data using the Friedman-Rafsky non-parametric test

2020 ◽  
Author(s):  
Yun Zhang ◽  
Brian D. Aevermann ◽  
Trygve E. Bakken ◽  
Jeremy A. Miller ◽  
Rebecca D. Hodge ◽  
...  
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Types ◽  
R Package ◽  
Brain Regions ◽  
Cortical Layer ◽  
Middle Temporal Gyrus ◽  
Cell Type ◽  
Sequencing Data

AbstractSingle cell/nucleus RNA sequencing (scRNAseq) is emerging as an essential tool to unravel the phenotypic heterogeneity of cells in complex biological systems. While computational methods for scRNAseq cell type clustering have advanced, the ability to integrate datasets to identify common and novel cell types across experiments remains a challenge. Here, we introduce a cluster-to-cluster cell type matching method – FR-Match – that utilizes supervised feature selection for dimensionality reduction and incorporates shared information among cells to determine whether two cell type clusters share the same underlying multivariate gene expression distribution. FR-Match is benchmarked with existing cell-to-cell and cell-to-cluster cell type matching methods using both simulated and real scRNAseq data. FR-Match proved to be a stringent method that produced fewer erroneous matches of distinct cell subtypes and had the unique ability to identify novel cell phenotypes in new datasets. In silico validation demonstrated that the proposed workflow is the only self-contained algorithm that was robust to increasing numbers of true negatives (i.e. non-represented cell types). FR-Match was applied to two human brain scRNAseq datasets sampled from cortical layer 1 and full thickness middle temporal gyrus. When mapping cell types identified in specimens isolated from these overlapping human brain regions, FR-Match precisely recapitulated the laminar characteristics of matched cell type clusters, reflecting their distinct neuroanatomical distributions. An R package and Shiny application are provided at https://github.com/JCVenterInstitute/FRmatch for users to interactively explore and match scRNAseq cell type clusters with complementary visualization tools.

scholarly journals Cellular and genetic drivers of RNA editing variation in the human brain

2021 ◽  
Author(s):  
Ryn Cuddleston ◽  
Junhao Li ◽  
Xuanjia Fan ◽  
Alexey Kozenkov ◽  
Matthew Lalli ◽  
...  
Keyword(s):  
Human Brain ◽  
Rna Sequencing ◽  
Rna Editing ◽  
Genetic Regulation ◽  
Cell Types ◽  
Brain Regions ◽  
Brain Cell ◽  
Cell Type ◽  
Sequencing Data ◽  
Regulatory Effects

Posttranscriptional adenosine-to-inosine modifications amplify the functionality of RNA molecules in the brain, yet the cellular and genetic regulation of RNA editing is poorly described. We quantified base-specific RNA editing across three major cell populations from the human prefrontal cortex: glutamatergic neurons, medial ganglionic eminence GABAergic neurons, and oligodendrocytes. We found more selective editing and RNA hyper-editing in neurons relative to oligodendrocytes. The pattern of RNA editing was highly cell type-specific, with 189,229 cell type-associated sites. The cellular specificity for thousands of sites was confirmed by single nucleus RNA-sequencing. Importantly, cell type-associated sites were enriched in GTEx RNA-sequencing data, edited ~twentyfold higher than all other sites, and variation in RNA editing was predominantly explained by neuronal proportions in bulk brain tissue. Finally, we discovered 661,791 cis-editing quantitative trait loci across thirteen brain regions, including hundreds with cell type-associated features. These data reveal an expansive repertoire of highly regulated RNA editing sites across human brain cell types and provide a resolved atlas linking cell types to editing variation and genetic regulatory effects.

scholarly journals A MAP of tumor-host interactions in glioma at single cell resolution

2019 ◽  
Author(s):  
Francesca Pia Caruso ◽  
Luciano Garofano ◽  
Fulvio D’Angelo ◽  
Kai Yu ◽  
Fuchou Tang ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Malignant Cells ◽  
Human Glioma ◽  
Sequencing Data ◽  
Host Interactions ◽  
Host Interaction ◽  
Receptor Interactions ◽  
Single Cell Rna Sequencing ◽  
Novel Method

ABSTRACTSingle-cell RNA sequencing is the reference technique to characterize the heterogeneity of tumor microenvironment and can be efficiently used to discover cross-talk mechanisms between immune cells and cancer cells. We present a novel method, single cell Tumor-Host Interaction tool (scTHI), to identify significantly activated ligand-receptor interactions across clusters of cells from single-cell RNA sequencing data. We apply our approach to uncover the ligand-receptor interactions in glioma using six publicly available human glioma datasets encompassing 71 patients. We provide a comprehensive map of the signalling mechanisms between malignant cells and non-malignant cells in glioma uncovering potential novel therapeutic targets.

scholarly journals FR-Match: robust matching of cell type clusters from single cell RNA sequencing data using the Friedman–Rafsky non-parametric test

2020 ◽  
Author(s):  
Yun Zhang ◽  
Brian D Aevermann ◽  
Trygve E Bakken ◽  
Jeremy A Miller ◽  
Rebecca D Hodge ◽  
...  
Keyword(s):  
Human Brain ◽  
Single Cell ◽  
Rna Sequencing ◽  
Cell Types ◽  
R Package ◽  
Brain Regions ◽  
Cortical Layer ◽  
Middle Temporal Gyrus ◽  
Cell Type ◽  
Sequencing Data

Abstract Single cell/nucleus RNA sequencing (scRNAseq) is emerging as an essential tool to unravel the phenotypic heterogeneity of cells in complex biological systems. While computational methods for scRNAseq cell type clustering have advanced, the ability to integrate datasets to identify common and novel cell types across experiments remains a challenge. Here, we introduce a cluster-to-cluster cell type matching method—FR-Match—that utilizes supervised feature selection for dimensionality reduction and incorporates shared information among cells to determine whether two cell type clusters share the same underlying multivariate gene expression distribution. FR-Match is benchmarked with existing cell-to-cell and cell-to-cluster cell type matching methods using both simulated and real scRNAseq data. FR-Match proved to be a stringent method that produced fewer erroneous matches of distinct cell subtypes and had the unique ability to identify novel cell phenotypes in new datasets. In silico validation demonstrated that the proposed workflow is the only self-contained algorithm that was robust to increasing numbers of true negatives (i.e. non-represented cell types). FR-Match was applied to two human brain scRNAseq datasets sampled from cortical layer 1 and full thickness middle temporal gyrus. When mapping cell types identified in specimens isolated from these overlapping human brain regions, FR-Match precisely recapitulated the laminar characteristics of matched cell type clusters, reflecting their distinct neuroanatomical distributions. An R package and Shiny application are provided at https://github.com/JCVenterInstitute/FRmatch for users to interactively explore and match scRNAseq cell type clusters with complementary visualization tools.

scholarly journals HEDGEHOG/GLI Modulates the PRR11-SKA2 Bidirectional Transcription Unit in Lung Squamous Cell Carcinomas

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 120
Author(s):  
Yiyun Sun ◽  
Dandan Xu ◽  
Chundong Zhang ◽  
Yitao Wang ◽  
Lian Zhang ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Squamous Cell ◽  
Gene Pair ◽  
Gene List ◽  
Ectopic Expression ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Gene Set

We previously demonstrated that proline-rich protein 11 (PRR11) and spindle and kinetochore associated 2 (SKA2) constituted a head-to-head gene pair driven by a prototypical bidirectional promoter. This gene pair synergistically promoted the development of non-small cell lung cancer. However, the signaling pathways leading to the ectopic expression of this gene pair remains obscure. In the present study, we first analyzed the lung squamous cell carcinoma (LSCC) relevant RNA sequencing data from The Cancer Genome Atlas (TCGA) database using the correlation analysis of gene expression and gene set enrichment analysis (GSEA), which revealed that the PRR11-SKA2 correlated gene list highly resembled the Hedgehog (Hh) pathway activation-related gene set. Subsequently, GLI1/2 inhibitor GANT-61 or GLI1/2-siRNA inhibited the Hh pathway of LSCC cells, concomitantly decreasing the expression levels of PRR11 and SKA2. Furthermore, the mRNA expression profile of LSCC cells treated with GANT-61 was detected using RNA sequencing, displaying 397 differentially expressed genes (203 upregulated genes and 194 downregulated genes). Out of them, one gene set, including BIRC5, NCAPG, CCNB2, and BUB1, was involved in cell division and interacted with both PRR11 and SKA2. These genes were verified as the downregulated genes via RT-PCR and their high expression significantly correlated with the shorter overall survival of LSCC patients. Taken together, our results indicate that GLI1/2 mediates the expression of the PRR11-SKA2-centric gene set that serves as an unfavorable prognostic indicator for LSCC patients, potentializing new combinatorial diagnostic and therapeutic strategies in LSCC.

RNA Sequencing Data from Human Intracranial Aneurysm Tissue Reveals a Complex Inflammatory Environment Associated with Rupture

2021 ◽  
Author(s):  
Vincent M. Tutino ◽  
Haley R. Zebraski ◽  
Hamidreza Rajabzadeh-Oghaz ◽  
Lee Chaves ◽  
Adam A. Dmytriw ◽  
...  
Keyword(s):  
Intracranial Aneurysm ◽  
Rna Sequencing ◽  
Sequencing Data
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